Academic literature on the topic 'Structural complexity index'

Objective: Project complexity is a crucial factor in project management that presents auxiliary obstacles to reaching project objectives (cost, time, safety, and quality). This study aims at understanding project complexity and factors affecting project complexity. The overall objective of the study is to determine the nature of complexity and characteristics, identify the important complex factors that influence the complexity of the project, factor weight of the complex factors, and develop a proposed construction complexity index (CCI). Methods: According to the literature review, the Analytic Hierarchy Process (AHP) method is used to measure the affecting factors of project complexity. Results: This paper developed an index to measure complexity based on factor weights called construction complexity index (CCI). The validity of this index was verified by studying 3 cases. The construction complexity index (CCI) proposed here allows measuring the complexity of the projects in Egypt. The results of this paper provide guidelines on how to successfully manage the complexity of the project. Conclusion: Project complexity management relates to the challenge of dealing with technical competence, professional diversity, uncertainties, and unforeseen events in project implementation. Project managers, who are critical to effectiveness or failure, need skills such as adaptation, creativity, and flexibility to meet this challenge. Therefore, this study provides guidelines to help practitioners to develop their capabilities in managing complex projects. Moreover, this paper enables participants to identify factors affecting the complexity of projects and how to calculate this complexity through the complex index. The outcomes of this study can be used by practitioners to develop a complexity assessment and management tool, which would enable industry practitioners to allocate resources effectively on complex construction projects. This research aimed to develop a measure by which the complexity of construction projects in Egypt can be evaluated and establish guidelines on avoiding complexity in projects.

This paper presents development of a multivariate forest structural complexity index based on relationships between field-based structural variables and geospatial data. Remote sensing has been widely used to model individual forest structural attributes at many scales. As opposed to, or in addition to, individual structural parameters such as leaf area index or tree height, overall structural complexity information can enhance forest inventories and provide a variety of information to forest managers, including identifying damage and disturbance as well as indicators of habitat or biodiversity. In this study, a multivariate modelling technique, redundancy analysis, was implemented to derive a model incorporating both horizontal and vertical structural attributes as predicted by an ensemble of high-resolution multispectral airborne imagery and topographic variables. The first redundancy analysis axis of the final model explained 35% of the total variance of the field variables and was used as the complexity index. With a root mean squared error of 19.9%, the model was capable of differentiating four to five relative levels of complexity. This paper presents the forest ecological and modelling aspects of the research. A related paper presents the remote sensing aspects, including application of the model to map predicted structural complexity, map validation, and testing of the method at multiple scales.

Abstract Applying the linear LAS (Latin American Structuralists) technological intensity model in Africa, this paper presents African nations are still diversifying their outputs towards the ubiquitous (fewer complexes) products. Put it simple, using the economic complexity index of Africa (explanatory variable) as a proxy for the technological intensity in Africa and per capita GDP gap (explanatory variable) as a proxy for technology gap, the paper presents a significant and positive relationship between economic complexity index of Africa and the time derivative of the economic complexity index of Africa (the explained variable). This implies that “weak” effort African nations exerted so far in diversifying their outputs towards the less ubiquitous commodities and absence of “automatic catch up tendency” (unlike what is presupposed by the mainstream neo-classical growth models). The linear panel data regression is employed on sample of 23 African economies and OECD member economies for the period 1996-2014.

Abstract Habitat structure is a factor that strongly affects the distribution of organisms. Habitats with high structural complexity provide a high number of microhabitats, allowing the coexistence of species with different behavioral, ecological and physiological requirements. We analyzed the effects of structural complexity of ponds on the number of males and foam nests of Physalaemus ephippifer, and the substrates to which individuals attach their foam nests. We sampled 41 ponds and recorded the number of individuals of P. ephippifer and environmental data (type of vegetation in, adjacent and around the pond; type of bottom substrate in the pond) to measure the degree of structural complexity of the ponds through an index ranging between 0 and 1. We found a positive influence of pond structural complexity on mean number of calling males, but not on number of foam nests. We found most foam nests attached to gramineans and herbaceous plants. Vegetation is an important component of habitats with high complexity, providing refuges for adults and tadpoles. The index was an efficient tool to measure habitat structural complexity, and may be used in further studies with other species.

Syntactic complexity in the movie retellings of 77 school-age Spanish-speaking children was examined using a structural constituent analysis. The results demonstrated developmental differences in the length of T-units, index of subordination, use of relative clauses, and prepositional phrases. There were also differences in the length of T-units, use of nominal clauses, and adverbial phrases across Spanish language groups. The analysis underscores the significance of subordination as a cohesive device and as an indicator of narrative proficiency.

In this paper, we study the complexity metrics for systematically generated assembly supply chains structures. We define three structural complexity indicators, such as the index of vertex degree, the supply chain length and the flow complexity. By a comparative study of 190 mathematically selected supply chain networks, we obtained Spearman correlation coefficients among three defined metrics and find some interesting results.

In this thesis I present and test a methodology for developing a stand scale index of structural complexity. If properly designed such an index can act as a summary variable for a larger set of stand structural attributes, providing a means of ranking stands in terms of their structural complexity, and by association, their biodiversity and vegetation condition. This type of index can also facilitate the use of alternative policy instruments for biodiversity conservation, such as mitigation banking, auctions and offsets, that rely on a common currency – the index value – that can be compared or traded between sites. My intention was to establish a clear and documentable methodology for developing a stand scale index of structural complexity, and to test this methodology using data from real stands.¶ As a starting point, I reviewed the literature concerning forest and woodland structure and found there was no clear definition of stand structural complexity, or definitive suite of structural attributes for characterising it. To address this issue, I defined stand structural complexity as a combined measure of the number of different structural attributes present in a stand, and the relative abundance of each of these attributes. This was analogous to approaches that have quantified diversity in terms of the abundance and richness of elements. It was also concluded from the review, that stand structural complexity should be viewed as a relative, rather than absolute concept, because the potential levels of different structural attributes are bound within certain limits determined by the inherent characteristics of the site in question, and the biota of the particular community will have evolved to reflect this range of variation. This implied that vegetation communities with naturally simple structures should have the potential to achieve high scores on an index of structural complexity.¶ I proposed the following five-stage methodology for developing an index of stand structural complexity: 1. Establish a comprehensive suite of stand structural attributes as a starting point for developing the index, by reviewing studies in which there is an established relationship between elements of biodiversity and structural attributes. 2. Develop a measurement system for quantifying the different attributes included in the comprehensive suite. 3. Use this measurement system to collect data from a representative set of stands across the range of vegetation condition (highly modified to unmodified) and developmental stages (regrowth to oldgrowth) occurring in the vegetation communities in which the index is intended to operate. 4. Identify a core set of structural attributes from an analysis of these data. 5. Combine the core attributes in a simple additive index, in which attributes are scored relative to their observed levels in each vegetation community.¶ Stage one of this methodology was addressed by reviewing a representative sample of the literature concerning fauna habitat relationships in temperate Australian forests and woodlands. This review identified fifty-five studies in south-east and south-west Australia, in which the presence or abundance of different fauna were significantly (p<0.05) associated with vegetation structural attributes. The majority of these studies concerned bird, arboreal mammal, and ground mammal habitat requirements, with relatively fewer studies addressing the habitat requirements of reptiles, invertebrates, bats or amphibians. Thirty four key structural attributes were identified from these fifty-five studies, by grouping similar attributes, and then representing each group with a single generic attribute. This set, in combination with structural attributes identified in the earlier review, provided the basis for developing an operational set of stand level attributes for the collection of data from study sites.¶ To address stages two and three of the methodology, data were collected from one woodland community –Yellow Box-Red Gum (E. melliodora-E. Blakelyi ) – and two dry sclerophyll forest communities – Broadleaved Peppermint-Brittle Gum (E. dives-E. mannifera ), Scribbly Gum-Red Stringybark (E. rossii E. macrorhyncha ) – in a 15,000 km2 study area in the South eastern Highlands Bioregion of Australia. A representative set of 48 sites was established within this study area, by identifying 24 strata, on the basis of the three vegetation communities, two catchments, two levels of rainfall and two levels of condition, and then locating two sites (replicates) within each stratum. At each site, three plots were systematically established, to provide an unbiased estimate of stand level means for 75 different structural attributes.¶ I applied a three-stage analysis to identify a core set of attributes from these data. The first stage – a preliminary analysis – indicated that the 48 study sites represented a broad range of condition, and that the two dry sclerophyll communities could be treated as a single community, which was structurally distinct from the woodland community. In the second stage of the analysis, thirteen core attributes were dentified using the criteria that a core attribute should:¶ 1. Be either, evenly or approximately normally distributed amongst study sites; 2. Distinguish between woodland and dry sclerophyll communities; 3. Function as a surrogate for other attributes; 4. Be efficient to measure in the field. The core attributes were: Vegetation cover <0.5m Vegetation cover 0.5-6.0m; Perennial species richness; Lifeform richness; Stand basal area of live trees; Quadratic mean diameter of live stems; ln(number of regenerating stems per ha+1); ln(number of hollow bearing trees per ha+1);ln(number of dead trees per ha+1);sqrt(number of live stems per ha >40cm dbh); sqrt(total log length per ha); sqrt(total largelog length per ha); Litter dry weight per ha. This analysis also demonstrated that the thirteen core attributes could be modelled as continuous variables, and that these variables were indicative of the scale at which the different attributes operated.¶ In the third and final stage of the analysis, Principal Components Analysis was used to test for redundancy amongst the core attributes. Although this analysis highlighted six groupings, within which attributes were correlated to some degree, these relationships were not considered sufficiently robust to justify reducing the number of core attributes.¶ The thirteen core attributes were combined in a simple additive index, in which, each attribute accounted for 10 points in a total index value of 130. Attributes were rescaled as a score from 0-10, using equations that modelled attribute score as a function of the raw attribute data. This maintained a high correlation (r > 0.97, p< 0.0001) between attribute scores and the original attribute data. Sensitivity analysis indicated that the index was not sensitive to attribute weightings, and on this basis attributes carried equal weight. In this form my index was straightforward to apply, and approximately normally distributed amongst study sites.¶ I demonstrated the practical application of the index in a user-friendly spreadsheet, designed to allow landowners and managers to assess the condition of their vegetation, and to identify management options. This spreadsheet calculated an index score from field data, and then used this score to rank the site relative to a set of reference sites. This added a regional context to the operation of the index, and is a potentially useful tool for identifying sites of high conservation value, or for identifying sites where management actions have maintained vegetation quality. The spreadsheet also incorporated the option of calculating an index score using a subset of attributes, and provided a measure of the uncertainty associated with this score.¶ I compared the proposed index with five prominent indices used to quantify vegetation condition or habitat value in temperate Australian ecosystems. These were: Newsome and Catling’s (1979) Habitat Complexity Score, Watson et al.’s (2001) Habitat Complexity Score, the Site Condition Score component of the Habitat Hectares Index of Parkes et al. (2003), the Vegetation Condition Score component of the Biodiversity Benefits Index of Oliver and Parkes (2003), and the Vegetation Condition Score component of the BioMetric Assessment Tool of Gibbons et al. (2004). I found that my index differentiated between study sites better than each of these indices. However, resource and time constraints precluded the use of a new and independent data set for this testing, so that the superior performance of my index must be interpreted cautiously.¶ As a group, the five indices I tested contained attributes describing compositional diversity, coarse woody debris, regeneration, large trees and hollow trees – these were attributes that I also identified as core ones. However, unlike these indices, I quantified weeds indirectly through their effect on indigenous plant diversity, I included the contribution of non-indigenous species to vegetation cover and did not apply a discount to this contribution, I limited the direct assessment of regeneration to long-lived overstorey species, I used stand basal area as a surrogate for canopy cover, I quantified litter in terms of biomass (dry weight) rather than cover, and I included the additional attributes of quadratic mean diameter and the number of dead trees.¶ I also concluded that Parkes et al. (2003), Oliver and Parkes (2003), and Gibbons et al. (2004), misapplied the concept of benchmarking, by characterising attributes in terms of a benchmark range or average level. This ignored processes that underpin variation at the stand level, such as the increased development of some attributes at particular successional stages, and the fact that attributes can respond differently to disturbance agents. It also produced indices that were not particularly sensitive to the differences in attribute levels occurring between stands. I suggested that a more appropriate application of benchmarking would be at the overarching level of stand structural complexity, using a metric such as the index developed in this thesis. These benchmarks could reflect observed levels of structural complexity in unmodified natural stands at different successional stages, or thresholds for structural complexity at which a wide range of biota are present, and would define useful goals for guiding on-ground management.

This thesis describes the development and setup of hybrid index structures. They are access methods for retrieval techniques in hybrid data spaces which are formed by one or more relational or normalised columns in conjunction with one non-relational or non-normalised column. Examples for these hybrid data spaces are, among others, textual data combined with geographical ones or data from enterprise content management systems. However, all non-relational data types may be stored as well as image feature vectors or comparable types. Hybrid index structures are known to function efficiently regarding retrieval operations. Unfortunately, little information is available about reorganisation operations which insert or update the row tuples. The fundamental research is mainly executed in simulation based environments. This work is written ensuing from a previous thesis that implements hybrid access structures in realistic database surroundings. During this implementation it has become obvious that retrieval works efficiently. Yet, the restructuring approaches require too much effort to be set up, e.g., in web search engine environments where several thousands of documents are inserted or modified every day. These search engines rely on relational database systems as storage backends. Hence, the setup of these access methods for hybrid data spaces is required in real world database management systems. This thesis tries to apply a systematic approach for the optimisation of the rearrangement algorithms inside realistic scenarios. Thus, a measurement and evaluation scheme is created which is repeatedly deployed to an evolving state and a model of hybrid index structures in order to optimise the regrouping algorithms to make a setup of hybrid index structures in real world information systems possible. Thus, a set of input corpora is selected which is applied to the test suite as well as an evaluation scheme. To sum up, it can be said that this thesis describes input sets, a test suite including an evaluation scheme as well as optimisation iterations on reorganisation algorithms reflecting a theoretical model framework to provide efficient reorganisations of hybrid index structures supporting multimedia search criteria.

The low frequency and often unique topographic setting of small circular stone ring structures of the late Paiján phase (ca. 11,200-9800 cal BP) necessitate a reconsideration of their nature and meaning at sites in several north coast valleys of Perú. It was previosly thought that they were exclusively domestic in function; however, it is now hypothesized that some may be multifunctional, including ritual activities.
La baja frecuencia y, a menudo, el único entorno topográfico en el que se encuentran muchas pequeñas estructuras de planta circular demarcadas con alineamientos de piedra de la fase Paiján Tardío (c. 11.200-9800 cal AP) hacen necesaria una reconsideraciónde su naturaleza y significado en los sitios correspondientes en varios valles de la costa norte del Perú. Con anterioridad se pensaba que estas estructuras eran exclusivamente domésticas respecto de su función; sin embargo, en la actualidad se pueden plantear hipótesis acerca de que algunas de ellas pudieron haber tenido un carácter multifuncional, lo que incluyó actividades rituales.

In this thesis I present and test a methodology for developing a stand scale index of structural complexity. If properly designed such an index can act as a summary variable for a larger set of stand structural attributes, providing a means of ranking stands in terms of their structural complexity, and by association, their biodiversity and vegetation condition. This type of index can also facilitate the use of alternative policy instruments for biodiversity conservation, such as mitigation banking, auctions and offsets, that rely on a common currency – the index value – that can be compared or traded between sites. My intention was to establish a clear and documentable methodology for developing a stand scale index of structural complexity, and to test this methodology using data from real stands.¶ ...

This thesis describes the development and setup of hybrid index structures. They are access methods for retrieval techniques in hybrid data spaces which are formed by one or more relational or normalised columns in conjunction with one non-relational or non-normalised column. Examples for these hybrid data spaces are, among others, textual data combined with geographical ones or data from enterprise content management systems. However, all non-relational data types may be stored as well as image feature vectors or comparable types. Hybrid index structures are known to function efficiently regarding retrieval operations. Unfortunately, little information is available about reorganisation operations which insert or update the row tuples. The fundamental research is mainly executed in simulation based environments. This work is written ensuing from a previous thesis that implements hybrid access structures in realistic database surroundings. During this implementation it has become obvious that retrieval works efficiently. Yet, the restructuring approaches require too much effort to be set up, e.g., in web search engine environments where several thousands of documents are inserted or modified every day. These search engines rely on relational database systems as storage backends. Hence, the setup of these access methods for hybrid data spaces is required in real world database management systems. This thesis tries to apply a systematic approach for the optimisation of the rearrangement algorithms inside realistic scenarios. Thus, a measurement and evaluation scheme is created which is repeatedly deployed to an evolving state and a model of hybrid index structures in order to optimise the regrouping algorithms to make a setup of hybrid index structures in real world information systems possible. Thus, a set of input corpora is selected which is applied to the test suite as well as an evaluation scheme. To sum up, it can be said that this thesis describes input sets, a test suite including an evaluation scheme as well as optimisation iterations on reorganisation algorithms reflecting a theoretical model framework to provide efficient reorganisations of hybrid index structures supporting multimedia search criteria.

Sizing up Consciousness explores, at an introductory level, the potential practical, clinical, and ethical implications of a general principle about the nature of consciousness. Using information integration theory (IIT) as a guiding principle, the book takes the reader along a scientific trajectory to face fundamental questions about the relationships between matter and experience. What is so special about a piece of flesh that can host a subject who sees light or experiences darkness? Why is the brain associated with a capacity for consciousness, but not the liver or the heart, as previous cultures believed? Why the thalamocortical system, but not other complicated neural structures? Why does consciousness fade during deep sleep, while cortical neurons remain active? Why does it recover, vivid, and intense, when the brain is disconnected from the external world during a dream? Can unresponsive patients with a functional island of cortex surrounded by widespread damage be conscious? Is a parrot that talks, or an octopus that learns and plays conscious? Can computers be conscious? Could a system behave like us and yet be devoid of consciousness—a zombie? The authors take on these basic questions by translating theoretical principles into anatomical observations, novel empirical measurements—such as an index of brain complexity that can be applied at the bedside of brain-injured patients—and thought experiments. The aim of the book is to describe, in an accessible way, a preliminary attempt to identify a general rule to size up the capacity for consciousness within the human skull and beyond.

Multilayer neural networks are commonly and frequently used technique for mapping complex nonlinear input-output relationship. However, they add more computational cost due to structural complexity in architecture. This chapter presents different functional link networks (FLN), a class of higher order neural network (HONN). FLNs are capable to handle linearly non-separable classes by increasing the dimensionality of the input space by using nonlinear combinations of input signals. Usually such network is trained with gradient descent based back propagation technique, but it suffers from many drawbacks. To overcome the drawback, here a natural chemical reaction inspired metaheuristic technique called as artificial chemical reaction optimization (ACRO) is used to train the network. As a case study, forecasting of the stock index prices of different stock markets such as BSE, NASDAQ, TAIEX, and FTSE are considered here to compare and analyze the performance gain over the traditional techniques.

The authors present two methods for examining video quality using the Structural Similarity (SSIM) index: Iterative Distortion Estimate (IDE) and Cumulative Distortion using SSIM (CDSSIM). In the first method, three types of slices are iteratively reconstructed frame-by-frame for three different combinations of packet loss and the resulting distortions are combined using their probabilities to give the total expected distortion. In the second method, a cumulative measure of the overall distortion is computed by summing the inter-frame propagation impact to all frames affected by a slice loss. Furthermore, the authors develop a No-Reference (NR) sparse regression framework for predicting the CDSSIM metric to circumvent the real-time computational complexity in streaming video applications. The two methods are evaluated in resource allocation and packet prioritization schemes and experimental results show improved performance and better end-user quality. The accuracy of the predicted CDSSIM values is studied using standard performance measures and a Quartile-Based Prioritization (QBP) scheme.

A skyline query retrieves all objects in a dataset that are not dominated by other objects according to some given criteria. There exist many skyline algorithms which can be classified into generic, index-based, and lattice-based algorithms. This chapter takes a tour through lattice-based skyline algorithms. It summarizes the basic concepts and properties, presents high-performance parallel approaches, shows how one overcomes the low-cardinality restriction of lattice structures, and finally presents an application on data streams for real-time skyline computation. Experimental results on synthetic and real datasets show that lattice-based algorithms outperform state-of-the-art skyline techniques, and additionally have a linear runtime complexity.

This chapter argues that money is data reified through financial systems, which in turn constitute and reflect dominant global power structures. Financial systems have hegemonic power over the ‘real economy’, significantly affecting the everyday lives of citizens. This is less data in society but rather data as society. Financial systems comprise a myriad of interacting actors and technologies. Financialisation is enabled through escalating debt and its securitisation, by which debt is turned into a tradeable commodity. The chapter gives examples of student debt and public service provision as examples of how our social lives are now determined by the operations of data-led financial markets. The scale and complexity of financial systems’ activities makes regulatory control and democratic accountability problematic. In particular, control over or regulation of financial systems requires access to data – transparency. The chapter discusses the manipulation of Libor – an important financial data index – and the tax system to explain how data in financial systems is relatively easy to manipulate and hide. In a globalised world, the interconnectedness, speed and scale of data all conspire to make finance a ‘dark domain’.

Agricultural product logistics is the key to ensuring people’s livelihood. The prediction of agricultural products’ logistics demand is an important guarantee for the rational planning of agricultural products logistics. However, the demand for agricultural product logistics is affected by many factors, which increases the complexity of its prediction. Therefore, taking the logistics demand of agricultural products as the research object, this paper constructs an index system from five aspects: the level of economic development, the level of industrial structure, the level of logistics development, the supply factors of agricultural products and human factors. Using the nonlinear mapping ability of the BP neural network, this paper constructs a BP neural network model to predict the logistics demand of agricultural products and takes the five provinces in North China as an example to predict the logistics demand of agricultural products. The results show that the established model has a strong ability to describe the nonlinear relationship between agricultural products logistics demand and its influencing factors, and can provide a basis for rational planning and policy-making of agricultural products logistics.

Hundreds of studies reveal than most cases of depression remain undetected and untreated. Yet there is growing concern that efforts to increase detection of depression entail unacceptable numbers of persons who are not depressed nonetheless being given a diagnosis and receiving medication. What factors underlie false-positive and false-negative errors? How might clinicians and services address these detection errors? Only about half of primary care practitioners (PCPs) feel confident in diagnosing depression or assessing suicide risk. Yet the issue of underdetection is by no means confined to PCPs or to depression. Convincing data show that clinicians in all medical specialties have difficulty recognizing mental disorders. This includes depression, anxiety, and delirium and dementia. Less discussed in the literature but increasingly recognized as important is the issue of overdetection. In this chapter I will review the predictors of diagnostic errors (false positives and false negatives) with reference to depression in primary care. I will focus on two essential barriers to correct identification: communication and illness complexity. To meaningfully discuss errors in recognition, it is important to first establish baseline rates of depression. Prevalence exerts a powerful influence upon detection accuracy, not least because clinicians usually have a higher index of suspicion for high-risk patients. The World Health Organization (WHO) study on Psychological Problems in General Health Care (PPGHC), conducted across 14 countries, found that 26% of individuals visiting their PCP had at least one psychiatric disorder as defined by ICD-10 criteria. Fourteen percent had major depression. Almost identical rates were reported from the European Study of the Epidemiology of Mental Disorders (ESEMeD). If one examines depression in older people, the point prevalence of major depression is lower in rural than urban primary care practices (8.3% versus 14.8%). Further, if one combines a 14% rate of major depression with 10% who have minor depression, then the combined rate approaches 25%. Approximately 100 studies concerning the unassisted recognition rate of depression in primary care have been published, but only a third have used a robust semi-structured interview as a gold standard.

<em>Abstract.</em>—Physical habitat degradation has been implicated as a major contributor to the historic decline of salmonids in Pacific Northwest streams. Native aquatic vertebrate assemblages in the Oregon and Washington Coast Range consist primarily of coldwater salmonids, cottids, and amphibians. This region has a dynamic natural disturbance regime, in which mass failures, debris torrents, fire, and tree-fall are driven by weather but are subject to human alteration. The major land uses in the region are logging, dairy farming, and roads, but there is disagreement concerning the effects of those activities on habitat and fish assemblages. To evaluate those effects, we examined associations among physical and chemical habitat, land use, geomorphology, and aquatic vertebrate assemblage data from a regional survey. In general, those data showed that most variation in aquatic vertebrate assemblage composition and habitat characteristics is predetermined by drainage area, channel slope, and basin lithology. To reveal anthropogenic influences, we first modeled the dominant geomorphic influences on aquatic biotic assemblages and physical habitat in the region. Once those geomorphic controls were factored out, associations with human activities were clarified. Streambed instability and excess fines were associated with riparian disturbance and road density, as was a vertebrate assemblage index of biotic integrity (IBI). Low stream IBI values, reflecting lower abundances of salmonids and other sediment-intolerant and coldwater fish and amphibian taxa, were associated with excess streambed fines, bed instability, higher water temperature, higher dissolved nutrient concentrations, and lack of deep pools and cover complexity. Anthropogenic effects were more pronounced in streams draining erodible sedimentary bedrock than in those draining more resistant volcanic terrain. Our findings suggest that the condition of fish and amphibian assemblages in Coast Range streams would be improved by reducing watershed activities that exacerbate erosion and mass-wasting of sediment; protecting and restoring multilayered structure and large, old trees in riparian zones; and managing landscapes so that large wood is delivered along with sediment in both natural and anthropogenic mass-wasting events. These three measures are likely to increase relative bed stability and decrease excess fines by decreasing sediment inputs and increasing energy-dissipating roughness from inchannel large wood and deep residual pools. Reducing sediment supply and transport to sustainable rates should also ensure adequate future supplies of sediment. In addition, these measures would provide more shade, bankside cover, pool volume, colder water, and more complex habitat structure.

In this paper we analyzed methods of investigating structure features in solid-state materials and developed a new algorithm for determining the surface structural complexity of these materials based on the two-dimensional detrended fluctuation analysis and the scale-space analysis. It is proposed to evaluate the surface structural complexity by calculating tangent of the angle of the fluctuation – spatial scale function and number of breakpoints on the fluctuation – spatial scale function. The developed algorithm was tested on the surface image of the Si layer implanted by Ag<sup>+<?sup> ions, subjected to the pulsed laser annealing. We found that investigated surface belongs to the type of surfaces with a high structural complexity. It was also shown that the scaling index – smoothing coefficient (scale) dependence can be used to study the dynamics of changes in the correlation properties of the surface. Knowledge about surface structural complexity of solid-state materials can be used to determine the material functional purpose in different fields of science.

With the rapid development of China’s chemical industry in coastal areas, the transportation of hazardous chemicals has become increasingly busy. Due to the complexity of marine environment, there are a large number of safety hazards during the transportation of hazardous chemicals. Based on accident statistics, the main factors affecting the transportation safety of hazardous chemicals is analyzed, including strong wind and reduced adhesion coefficient caused by rain and snow. Further, a vehicle stability analysis model considering these factors is established to calculate the critical wind speed of sideslip. Finally, the speed of the hazardous chemical vehicle is used as the safety evaluation index, and the safety critical speed surface is given. This research has important reference value for ensuring the transportation safety of hazardous chemicals and the operation of cross-sea bridges.

In this study we investigated the communities of soil nematodes in the forest habitats invaded and uninvaded by Fallopia japonica (Houtt.) Ronse Decr., in Tatra National Park, Slovakia. We found that invasion by F. japonica altered nematode communities and their structures. Total nematode abundance, species number and nematode biomass were significantly lower in invaded than uninvaded plots, but species diversity remained unaffected throughout the study. The overall abundance of all nematode trophic groups well represented the negative impact of F. japonica invasion on soil food webs, supported by low values of all maturity indices, a structural index and the Jaccard index of faunal similarity. A weighted faunal analysis similarly characterized the food webs of invaded plots as poorly developed or highly disturbed, with bacterial decomposition and a low C/N ratio. Our findings thus suggest that dense plots of knotweed simplify the structural complexity of the soil environment by reducing the richness of plant species, which may have contributed to the negative changes in the structures of the nematode communities.

Abstract In this study, we present USDL, a novel model that employs deep learning algorithms in order to reconstruct and enhance corrupted ultrasound images. We utilize an unsupervised neural network called an autoencoder which works by compressing its input into a latent-space representation and then reconstructing the output from this representation. We trained our model on a dataset that compromises of 15,700 in vivo images of the neck, wrist, elbow, and knee vasculature and compared the quality of the images generated using the structural similarity index (SSIM) and peak to noise ratio (PSNR). In closely simulated conditions, the architecture exhibited an average reconstruction accuracy of 90% as indicated by our SSIM. Our study demonstrates that USDL outperforms state of the art image enhancement and reconstruction techniques in both image quality and computational complexity, while maintaining the architecture efficiency.

Cylindrical Shells are widely used in many structural designs, such as offshore structures, liquid storage tanks, submarine hulls, and airplane hulls. Most of these structures are required to operate in a dynamic environment. Therefore, investigating the dynamic characteristics of cylindrical shells is very critical in developing a strategy for modal vibration control for specific operating conditions. Reduction of vibration amplitudes and in sound radiation is most efficiently achieved at the design stage, and the acoustic signatures may be determined by considering operational scenarios, and modal characteristics. In cylindrical shells, mode shapes associated with each natural frequency are combination of Radial, Longitudinal, and Circumferential modes, and unlike those of beam structure, the lowest natural frequency does not necessarily correspond to the lowest wave index. In fact, the natural frequencies do not fall in ascending order of the wave index in cylindrical shells. The ratio of membrane strain energy to total strain energy is high for modes with simple modal patterns and decrease toward zero as the number of nodal (n) lines increase, while the ratio of bending energy to total strain energy is small for simple nodal patterns and increase with increase in complexity of it. Modes associated with membrane deformation require a lot of strain energy while modes associated with bending deformation require less strain energy. The lowest natural frequency occurs where the sum of the two energies are at minimum. Moreover, the natural frequencies that are controlled by membrane strain energy are approximately independent of the shell thickness change. In this paper, a scaled model of submarine hull segment under shear diaphragm boundary conditions is analyzed analytically and numerically. Then the experimental modal analysis of the scaled model utilizing strain gauges was performed to decouple the strain components. Designing a boundary condition that simulate a shear diaphragm is very challenging task by itself. The experimental data were correlated with those results obtained analytically and numerically using the finite element methods using MSC.NASTRAN software. The results were found to be in excellent agreement.