Insufficient Data Availability Research Articles

Simulating Urban Land Expansion in the Context of Land Use Planning in the Abuja City-Region, Nigeria

In the Global South, including the Sub-Saharan African city-regions, the possible future urban expansion patterns may pose a challenge towards improving environmental sustainability. Land use planning strategies and instruments for regulating urban expansion are faced with challenges, including insufficient data availability to offer insights into the possible future urban expansion. This study integrated empirical data derived from Geographic Information Systems, Remote Sensing, and surveys of experts to offer insights into the possible future urban expansion under spatial planning scenarios to support land use planning and environmental sustainability of city-regions. We analyzed the spatial determinants of urban expansion, calibrated the land cover model using the Multi-Layer Perceptron Neural Network and Markov, and developed three scenarios to simulate land cover from 2017 to 2030 and to 2050. The scenarios include Business As Usual that extrapolates past trends; Regional Land Use Plan that restricts urban expansion to the land designated for urban development, and; Adjusted Urban Land that incorporates the leapfrogged settlements into the land designated for urban development. Additionally, we quantified the potential degradation of environmentally sensitive areas by future urban expansion under the three scenarios. Results indicated a high, little, and no potential degradation of environmentally sensitive areas by the future urban expansion under the Business As Usual, Adjusted Urban Land, and Regional Land Use Plan scenarios respectively. The methods and the baseline information provided, especially from the Adjusted Urban Land scenario showed the possibility of balancing the need for urban expansion and the protection of environmentally sensitive areas. This would be useful to improve the environmental sustainability of the Sub-Saharan African city-regions and across the Global South, where insufficient data availability challenges land use planning.

Elucidating the Impact of Immunogenicity Assessment Postapproval: A Targeted Analysis of Immunogenicity Postmarketing Requirements and Commitments.

Insufficient availability of data to evaluate immunogenicity incidence or clinical impact during regulatory review could require further evaluation postapproval. Through a keyword search of all postmarketing requirements and commitments (PMRs/PMCs) associated with products with their original US Food and Drug Administration (FDA) approvals between 2009 and 2018, we identified products that had PMRs/PMCs established to address concerns or uncertainty related to immunogenicity. Of the 113 relevant products, 50% had an immunogenicity-related PMR/PMC; of these, 68% were related to developing immunogenicity assays and 48% requested an assessment of clinical impact. Fifty-five percent of the products with a fulfilled PMR/PMC had a change in the immunogenicity information in their labeling immediately following fulfillment. This work highlights that there are often unknowns associated with immunogenicity incidence and/or impact at the time of approval. Earlier regulatory discussions on immunogenicity assessments in premarket development could improve the understanding and communication of the risk/benefit profile and reduce the need for some immunogenicity PMRs/PMCs.

Uncovering Spatial Invasion on Metapopulation Networks with SIR Epidemics

Understanding how infectious diseases spatially diffuse is critical to predict and control the epidemic prevalence. However, uncovering epidemic spatial invasion is challenging due to stochastic travel of hosts and insufficient data availability. In this study, we develop a methodology for inferring global invasion pathways on metapopulation networks with the susceptible-infected-recovered (SIR) epidemics. To solve the inference problem, we infer the invasion pathways of each invasion case as a subgraph containing a part of global invasion pathways at each epidemic arrival time. We first develop a reduction approach to decrease the sizes of the dominant invasion cases, and propose a local optimization method aiming at the SIR epidemics based on epidemic maximum diffusion (EMD) to infer spatial invasion pathways of the reduced invasion cases, and reconstruct the global invasion pathways. Compared with the previous work, we reduce the computational complexity of invasion cases, and improve the calculation of epidemic diffusion likelihood and effectiveness of the algorithm for epidemic recovery. Simulations on real and synthetic metapopulation networks verify the validity of our algorithm. Finally, an empirical example of the 2009 A (H1N1) in the USA is presented to uncover the spatial invasion pathways and identify the superinvader s.

Variability of Thermohaline Characteristics at 26.5° N in Reanalyses and Oceanographic Section Data

The most common methods for studying the variability of ocean parameters are field measurements and numerical modeling. Due to the insufficient availability of ocean measurement data, it is not always possible to verify the reliability of modeling results. Changes in temperature and salinity of the Atlantic Ocean water masses at 26.5° N in the recent 30 and 70 years are estimated. The estimation is based on the data of SODA, ORAS4, ECCO, GECCO reanalyses, EN4 and WOA13 objective analyses, and six regular oceanographic sections. In 1992 to 2016, all reanalyses simulate an increase in temperature and salinity of surface water for the entire section, which is consistent with field data. On average, the reanalyses overestimate temperature by 0.1–0.3°C and salinity by 0.02–0.05 psu. The closest values to field data are reproduced by the ORAS4 reanalysis and EN4 objective analysis. Trends in temperature and salinity coincide best with the EN4 results.

Experimental study on the hydrodynamic behavior of gas-liquid air-water two-phase flow near the transition to slug flow in horizontal pipes

The knowledge of the slug flow is essential the design safety of hydrocarbon transportation in the pipeline system of petroleum industries. However, the suitable models to predict the transition condition to slug flow are limited due to insufficient availability of experimental data. In the present study, the hydrodynamic characteristics of the near the transition to slug flow of air-water two-phase flow in horizontal pipes were investigated experimentally for inner pipe diameters of 16 mm, 26 mm, and 50 mm. The superficial velocities of water and air ranged from JL = 0.03 to 0.30 m/s and JG = 0.7 to 10.0 m/s. The hydrodynamic behavior was obtained from the combination of the visualization detected by using a high-speed video camera, the pressure gradient, and instantaneous volumetric liquid fraction measurements.The experimental results indicate that the wave growth and the wave coalescence are involved in the mechanism of the slug flow formation. Both gas and liquid superficial velocities have a significant effect also of those mechanisms. The average volumetric liquid fraction near the transition to slug flow is not affected by superficial gas velocities. Next, under a constant superficial gas velocity, an increase in the inner pipe diameter requires a larger superficial liquid velocity to change the flow patterns from stratified smooth to slug flow, and from pseudo-slug to slug flow.

Compositional and predicted functional analysis of the gut microbiota of Radix auricularia (Linnaeus) via high-throughput Illumina sequencing.

Due to its wide distribution across the world, the snail Radix auricularia plays a central role in the transferal of energy and biomass by consuming plant biomass in freshwater systems. The gut microbiota are involved in the nutrition, digestion, immunity, and development of snails, particularly for cellulolytic bacteria, which greatly contribute to the digestion of plant fiber. For the first time, this study characterized the gut bacterial communities of R. auricularia, as well as predicted functions, using the Illumina Miseq platform to sequence 16S rRNA amplicons. Both juvenile snails (JS) and adult snails (AS) were sampled. The obtained 251,072 sequences were rarefied to 214,584 sequences and clustered into 1,196 operational taxonomic units (OTUs) with 97% sequence identity. The predominant phyla were Proteobacteria (JS: 36.0%, AS: 31.6%) and Cyanobacteria (JS: 16.3%, AS: 19.5%), followed by Chloroflexi (JS: 9.7%, AS: 13.1%), Firmicutes (JS: 14.4%, AS: 6.7%), Actinobacteria (JS: 8.2%, AS: 12.6%), and Tenericutes (JS: 7.3%, AS: 6.2%). The phylum Cyanobacteria may have originated from the plant diet instead of the gut microbiome. A total of 52 bacterial families and 55 genera were found with >1% abundance in at least one sample. A large number of species could not be successfully identified, which could indicate the detection of novel ribotypes or result from insufficient availability of snail microbiome data. The core microbiome consisted of 469 OTUs, representing 88.4% of all sequences. Furthermore, the predicted function of bacterial community of R. auricularia performed by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States suggests that functions related to metabolism and environmental information processing were enriched. The abundance of carbohydrate suggests a strong capability of the gut microbiome to digest lignin. Our results indicate an abundance of bacteria in both JS and AS, and thus the bacteria in R. auricularia gut form a promising source for novel enzymes, such as cellulolytic enzymes, that may be useful for biofuel production. Furthermore, searching for xenobiotic biodegradation bacteria may be a further important application of these snails.

Spatial and temporal patterns of human Puumala virus (PUUV) infections in Germany.

BackgroundWorldwide, the number of recorded human hantavirus infections as well as the number of affected countries is on the rise. In Europe, most human hantavirus infections are caused by the Puumala virus (PUUV), with bank voles (Myodes glareolus) as reservoir hosts. Generally, infection outbreaks have been related to environmental conditions, particularly climatic conditions, food supply for the reservoir species and land use. However, although attempts have been made, the insufficient availability of environmental data is often hampering accurate temporal and spatially explicit models of human hantavirus infections.MethodsIn the present study, dynamics of human PUUV infections between 2001 and 2015 were explored using ArcGIS in order to identify spatio-temporal patterns.ResultsPercentage cover of forest area was identified as an important factor for the spatial pattern, whereas beech mast was found explaining temporal patterns of human PUUV infections in Germany. High numbers of infections were recorded in 2007, 2010 and 2012 and areas with highest records were located in Baden-Wuerttemberg (southwest Germany) and North Rhine-Westphalia (western Germany).ConclusionMore reliable data on reservoir host distribution, pathogen verification as well as an increased awareness of physicians are some of the factors that should improve future human infection risk assessments in Germany.

Enabling Data Analytics in Large Scale Manufacturing

Companies of the manufacturing industry face increasing process complexity. To remain competitive, increasing the knowledge concerning innovative manufacturing processes is necessary. In other areas, data analytics methods have been successfully applied for this purpose. Currently, their application in large scale manufacturing is hampered by insufficient data availability. Therefore, this study presents a solution approach that enables adaptive data availability by establishing a data-use-case-matrix (DUCM), which allows use case prioritization to support dimensioning of control systems and IT infrastructures. In order to support technology development, further proposed is a scalable implementation of the prioritized use cases starting in early prototyping phases.

Constructing the PD Term Structure

With the ongoing implementation of the IFRS 9 impairment framework increasing attention is paid to a consistent determination of expected credit lifetime losses. A clear distinction between point-in-time (PIT) and through-the-cycle (TTC) credit default probabilities is well known to be crucial for the construction of suitable PD term structures. However, due to typically insufficient data availability and quality the most widely spread approach to the PD term structure construction, i.e. the Exponentiation Approach, still relies on the exponentiation of observed one-year migration matrices irrespective of whether these are derived in a PIT- or TTC-context. In this paper the authors discuss the source of the conceptual inadequacy of this frequently used approach. Addressing these shortcomings, a new and conceptually consistent approach to deriving the genuine PD term structure is introduced and the fixation of its underlying model parameters is benchmarked on synthetic migration time series. This new method, which will be called Consistent Approach, allows in particular to estimate the dependence of the genuine PD term structure on the macroeconomic starting condition, rendering it applicable to both regulatory and internal stress testing. Finally, both the Exponentiation Approach and the Consistent Approach outlined in this paper are applied to actual migration data provided by GCD, the Global Credit Data consortium, allowing to observe the quantitative impact on PD term structure curves and thus on lifetime expected loss estimates. A profound impact on the term structure is found when comparing the market-standard Exponentiation Approach and the newly developed Consistent Approach.

A simulation-based water-environment management model for regional sustainability in compound wetland ecosystem under multiple uncertainties

In this study, a simulation-based water-environment management model with Laplace scenario analysis (SWML) is developed for planning regional sustainability in compound wetland ecosystem. SWML can not only deal with spatial and temporal variations of hydrologic elements within the watershed, but also handle multiple uncertainties presented in terms of probability, possibility distributions, and fuzzy sets. Meanwhile, policy scenario analysis with Laplace's criterion (PSL) is introduced to handle probability of each scenario occurrence under insufficient data availability. The developed SWML is applied to water-environment management in Xixian wetland (located in north of China), where a compound wetland ecosystem (CWE) would be embedded into the concept of eco-county to remit contradiction between human activity and environmental issue through ecological mechanism. Results of ecological effect, water allocation pattern, pollution mitigation scheme and system benefit under various scenarios are obtained, which can support policymakers adjusting current plan with a cost-effective and sustainable manner. Meanwhile, satisfaction degrees for constraints using necessity levels and Laplace's criterions can support generating a robust plan associated with risk control for regional sustainability in CWE under uncertainties. The findings can support building a new construction of integrated human being–ecological environment system, which is beneficial to achieve integrity of socioeconomic development and eco-environmental sustainability.

NIMG-33CORRELATING A PATIENT-SPECIFIC MATHEMATICAL MODEL OF GLIOBLASTOMA PROLIFERATION-INVASION WITH IMAGE-GUIDED BIOPSIES

Glioblastoma is an invasive disease with cancerous cells extending well beyond the margin of the imaging abnormalities. The degree of invasiveness, however, is heterogeneous amongst the patient population. Previous work with a patient-specific mathematical model has shown that a mathematically intuitive understanding of individual invasiveness based on matching patients' T1Gd and T2 abnormalities with 80% and 16% tumor cell density respectively is predictive of IDH1 mutation status, degree of hypoxia, and overall survival benefit due to resection. Direct validation of the tumor cell density prediction has not been possible due to insufficient data availability. Over the last few years, a cohort of patients at Columbia University have been recruited to have MRI guided biopsies just prior to their tumor resections allowing for a known correspondence between tissue and MRI characteristics. Seven of these patients have been analyzed in both contexts of the mathematical model and biopsy cell counts. Their images were analyzed with the model to create individualized predictions of the patients' tumor cell density. In parallel, biopsy specimens were prepared with H&E stains and total cell counts were obtained from representative portions of the prepared slide when viewed at 400x magnification. Cell counts were compared to density predictions corresponding to the biopsy location's distance from the edge of the measured T1Gd abnormality. The median number of biopsies used for comparison from each patient was 2 (range 1-4). In total, cell counts from 16 biopsies were obtained. Allowing for sources of error in both the model prediction and the biopsy acquisition location, all 16 cell counts were consistent with the model's prediction of tumor cell density. While this is certainly not enough evidence to conclusively determine the validity of the model, these results support a direct interpretation of individualized cell density model predictions beyond the T1Gd imaging abnormality.

S03.4 Future directions for global sti estimates

Background Estimating STI prevalence and incidence are important for programming and advocacy. Current global and regional estimates are based on meta-analysis of prevalence data of gonorrhoea, chlamydia and trichomoniasis among low-risk populations, and on national surveillance of syphilis sero-prevalence among antenatal care attendees, with adjustment for laboratory test types, geography and age. The precision and utility of these estimates is limited by insufficient, varying, and uncertain data availability and quality, notably on duration of infection and symptoms, representativeness of survey samples, etc. Current estimation methods are not able to incorporate data from high risk populations and are not able to generate national STI estimates. The Spectrum suite of estimation and program planning tools has been developed to support estimation of burdens, trends, service needs and program impact for family planning, HIV/AIDS, tuberculosis and other diseases. The HIV/AIDS, Spectrum is used by over 120 countries every two years to estimate their burden of HIV/AIDS, antiretroviral treatment need and other services. Next generation of estimating STIs A module for estimating burdens and trends of STIs in the Spectrum suite of health modelling tools is being developed, initially for gonorrhoea and syphilis, for which relatively good and abundant country data are available. The Spectrum module will fit STI burdens and trends using standard STI indicators collected routinely by countries and reported annually to the WHO and UNAIDS through the Global AIDS Response Progress Reporting (GARPR) system and STI data on general populations from peer-reviewed literature. By building onto the HIV/AIDS model within Spectrum, the STI estimation tool will benefit from efficiency, expertise, coherence and consistency with estimations of HIV/AIDS. Next steps The development and piloting of the Spectrum STI module is a first phase towards supporting country-level STI estimation and program planning. The STI module will be implemented in selected countries in. two-yearly cycle of country consultations tagged into the UNAIDS HIV/AIDS estimation. A companion module for strategic STI intervention modelling, program planning and costing – as an extension to Spectrum’s current One Health Tool representation of MNCH, family planning and HIV primary/behavioural prevention programs will be designed and developed.

Heuristic techniques to optimize neural network architecture in manufacturing applications

Nowadays application of neural networks in the manufacturing field is widely assessed even if this type of problem is typically characterized by an insufficient availability of data for a robust network training. Satisfactory results can be found in the literature, in both forming and machining operations, regarding the use of a neural network as a predictive tool. Nevertheless, the research of the optimal network configuration is still based on trial-and-error approaches, rather than on the application of specific techniques . As a consequence, the best method to determine the optimal neural network configuration is still a lack of knowledge in the literature overview. According to that, a comparative analysis is proposed in this work. More in detail four different approaches have been used to increase the generalization abilities of a neural network. These methods are based, respectively, on the use of genetic algorithms, Taguchi, tabu search and decision trees. The parameters taken into account in this work are the training algorithm, the number of hidden layers, the number of neurons and the activation function of each hidden layer. These techniques have been firstly tested on three different datasets, generated through numerical simulations in the Deform2D environment, in an attempt to map the input---output relationship for an extrusion, a rolling and a shearing process. Subsequently, the same approach has been validated on a fourth dataset derived from the literature review for a complex industrial process to widely generalize and asses the proposed methodology in the whole manufacturing field. Four tests were carried out for each dataset modifying the original data with a random noise with zero mean and standard deviation of one, two and five per cent. The results show that the use of a suitable technique for determining the architecture of a neural network can generate a significant performance improvement compared to a trial-and-error approach.

Conflict resolution measures for connection dispatching

In this paper we present conflict resolution measures in connection dispatching suitable for railway transportation companies without having full access to relevant data. The presented measures do not only cover classical waiting/non-waiting-strategies but also alternative dispatching measures if a distributor train cannot wait. The fact of unknown travel chains and insufficient data availability is respected. Different solutions for a connection conflict are generated depending on travel destinations.Conflict resolution measures are divided into those that can be applied within the railway system and those that are outside the railway system. Each of the considered measures has been analysed by the use of a formalized procedure to get a structured prospect on background, impact, operability, compatibility and quantifying parameters. The procedure is explained by giving several examples. Finding conflict solutions, the focus is to achieve the highest possible completeness regarding potential solutions. At the same time, to reduce computing time, heuristic approaches are applied. The presented measures enable transportation companies to implement a system which calculates conflict resolution proposals to support the connection dispatching staff. This leads to a more automated, more transparent and more efficient dispatching process which results in more satisfied travellers.

Benchmarking of industrial park infrastructures in Germany

Purpose – The purpose of this paper is to evaluate the operational performance of industrial park infrastructures in Germany to find first indications for cost saving potentials. Design/methodology/approach – Between 2006 and 2007, six chemical parks and chemical related industrial parks in Germany participated in a benchmarking study with focus on operation and maintenance of buildings, communication infrastructures and traffic infrastructures. Based on data analysis in combination with workshops, numerous key performance indicators were defined and calculated. Findings – To compare the different complexities of the analysed infrastructures, the most important key performance indicators were adjusted using correction factors defined and verified during the workshops. This made a discussion based on comparable and comprehensible figures possible which increased the acceptance and applicability of the benchmarking methodology. The benchmarking results showed large differences in performance levels, indicating that there are significant cost saving potentials in some industrial parks. Research limitations/implications – The comparability may remain limited due to the partly insufficient availability of data from the participants. Other limitations are due to the small number of investigated industrial parks and the focus of the benchmarking study on Germany. Originality/value – The developed benchmark and best practice methodology is well suited to evaluate best practice in the field of industrial park infrastructures. It is important for industrial parks to understand the individual performance level and to adapt best practice in all areas.

Database Generation for the Development of Village Information System (VIS)

According to Mahatma Gandhiji village is a backbone of our nation. In planning and development process village should be at the centre. Village information system (VIS) is a micro level study which may helpful to planners, policy makers and administrators in planning and decision making process. It is seen that may planning gets fail due to insufficient and non availability of data. Data is considered as raw material from which meaningful results and analysis can be carried out. Database is a group of organized records and files which are stored systematically and shared by different users. To generate an information system it requires lot of data and database integrated with GIS. Comprehensive village level information system is a need of hour and in this system database generation is a prime task. Microsoft Access is a low cost, widely available relational database management system (RDBMS) used mainly by home and small business users. Therefore in this paper an attempt is made to highlight the process of database generation for the development of VIS using MS-Access.

The cytochrome c peroxidase and cytochrome c encounter complex: the other side of the story.

Formation of an encounter complex is important for efficient protein complex formation. The encounter state consists of an ensemble of orientations of two proteins in the complex. Experimental description of such ensembles inherently suffers from insufficient data availability. We have measured paramagnetic relaxation enhancements (PRE) on cytochrome c peroxidase (CcP) caused by its partner cytochrome c (Cc) carrying a spin label. The data complement earlier PRE data of spin labelled CcP, identifying several new interactions. This work demonstrates the need of obtaining as many independent data sets as possible to achieve the most accurate description of an encounter complex.

A morphogenetic survey on ciliate plankton from a mountain lake pinpoints the necessity of lineage‐specific barcode markers in microbial ecology

Analyses of high-throughput environmental sequencing data have become the ‘gold-standard’ to address fundamental questions of microbial diversity, ecology and biogeography. Findings that emerged from sequencing are, e.g. the discovery of the extensive ‘rare microbial biosphere’ and its potential function as a seed-bank. Even though applied since several years, results from high-throughput environmental sequencing have hardly been validated. We assessed how well pyrosequenced amplicons [the hypervariable eukaryotic V4 region of the small subunit ribosomal RNA (SSU rRNA) gene] reflected morphotype ciliate plankton. Moreover, we assessed if amplicon sequencing had the potential to detect the annual ciliate plankton stock. In both cases, we identified significant quantitative and qualitative differences. Our study makes evident that taxon abundance distributions inferred from amplicon data are highly biased and do not mirror actual morphotype abundances at all. Potential reasons included cell losses after fixation, cryptic morphotypes, resting stages, insufficient sequence data availability of morphologically described species and the unsatisfying resolution of the V4 SSU rRNA fragment for accurate taxonomic assignments. The latter two underline the necessity of barcoding initiatives for eukaryotic microbes to better and fully exploit environmental amplicon data sets, which then will also allow studying the potential of seed-bank taxa as a buffer for environmental changes.

International Married and Unmarried Unions in Italy: Criteria of Mate Selection

AbstractAs a result of the growing presence of foreign immigrants settling in Italy, recent years have seen a significant increase in the number of mixed unions. However, little research has been carried out on the subject in this country, in part due to insufficient availability of suitable data. The aim of this study is to investigate the “market” of formal and informal mixed unions and to understand whether ethnic origin contributes a new element to the marriage/union market, and to verify the applicability of the “exchange theory” to the Italian context. We analyzed a particular segment of the marriage market ‐ mixed parental couples included in the 2005 Sample Surveys of Births. The results showed a clear gender divide in the ethnic preferences of Italian spouses, a high rate of previous marital experience for both Italian and foreign people in mixed pairings, and a high frequency of unmarried and casual mixed relationships. Compared with endogamous couples, the foreign male or female spouse/partner in mixed couples is young and more educated relative to the Italian partner, but is less present in the work market and, when employed, often occupies a less well‐qualified position. The “informal union market” works in very similar ways to the “marriage market”; the slight attenuation of relationships observed in the former being attributable to the lesser degree of security guaranteed by an unofficial union. Therefore, the mechanism of mate selection implies that foreigners' appreciated qualities such as youth and high education may be offered in exchange for economic security, upward socio‐economic mobility and access to the social network of the native partner: this is a variant of the exchange theory that was found to apply well to transnational marriages/unions in Italy.

Multiscale Mechanics of Articular Cartilage: Potentials and Challenges of Coupling Musculoskeletal, Joint, and Microscale Computational Models

Articular cartilage experiences significant mechanical loads during daily activities. Healthy cartilage provides the capacity for load bearing and regulates the mechanobiological processes for tissue development, maintenance, and repair. Experimental studies at multiple scales have provided a fundamental understanding of macroscopic mechanical function, evaluation of the micromechanical environment of chondrocytes, and the foundations for mechanobiological response. In addition, computational models of cartilage have offered a concise description of experimental data at many spatial levels under healthy and diseased conditions, and have served to generate hypotheses for the mechanical and biological function. Further, modeling and simulation provides a platform for predictive risk assessment, management of dysfunction, as well as a means to relate multiple spatial scales. Simulation-based investigation of cartilage comes with many challenges including both the computational burden and often insufficient availability of data for model development and validation. This review outlines recent modeling and simulation approaches to understand cartilage function from a mechanical systems perspective, and illustrates pathways to associate mechanics with biological function. Computational representations at single scales are provided from the body down to the microstructure, along with attempts to explore multiscale mechanisms of load sharing that dictate the mechanical environment of the cartilage and chondrocytes.