bluuebunny/crossref_metadata_2025 huggingface dataset:
Homogeneity Distance Classification Algorithm (HDCA): A Novel Algorithm for Satellite Image Classification
Authors: Firozjaei Mohammad Karimi , Daryaei Iman , Sedighi Amir , Weng Qihao , Alavipanah Seyed Kazem
Published: March 2019

Image classification is one of the most common methods of information extraction from satellite images. In this paper, a novel algorithm for image classification based on gravity theory was developed, which was called “homogeneity distance classification algorithm (HDCA)”. The proposed HDCA used texture and spectral information for classifying images in two iterative supplementary computing stages: (1) merging, (2) traveling and escaping operators. The HDCA was equipped by a new concept of distance, the weighted Manhattan distance (WMD). Moreover, an improved gravitational search algorithm (IGSA) was applied for selecting features and determining optimal feature space scale in HDCA. In the case of multispectral satellite image classification, the proposed method was compared with two well-known classification methods, Maximum Likelihood classifier (MLC) and Support Vector Machine (SVM). The results of the comparison indicated that overall accuracy values for HDCA, MLC, and SVM are 95.99, 93.15, and 95.00, respectively. Furthermore, the proposed HDCA method was also used for classifying hyperspectral reference datasets (Indian Pines, Salinas and Salinas-A scene). The classification results indicated substantial improvement over previous algorithms and studies by 2% in Indian Pines dataset, 0.7% in the Salinas dataset and 1.2% in the Salinas-A scene. These experimental results demonstrate that the proposed algorithm can classify both multispectral and hyperspectral remote sensing images with reliable accuracy because this algorithm uses the WMD in the classification process and the IGSA to select automatically optimal features for image classification based on spectral and texture information.
Processing Thermal Infrared Imagery Time-Series from Volcano Permanent Ground-Based Monitoring Network. Latest Methodological Improvements to Characterize Surface Temperatures Behavior of Thermal Anomaly Areas
Authors: Sansivero Fabio , Vilardo Giuseppe
Published: March 2019

In this technical paper, the state-of-art of automated procedures to process thermal infrared (TIR) scenes acquired by a permanent ground-based surveillance system, is discussed. TIR scenes regard diffuse degassing areas at Campi Flegrei and Vesuvio in the Neapolitan volcanic district (Italy). The processing system was developed in-house by using the flexible and fast processing Matlab© environment. The multi-step procedure, starting from raw infrared (IR) frames, generates a final product consisting mainly of de-seasoned temperatures and heat fluxes time-series as well as maps of yearly rates of temperature change of the IR frames. Accurate descriptions of all operational phases and of the procedures of analysis are illustrated; a Matlab© code (Natick, MA, USA) is provided as supplementary material. This product is ordinarily addressed to study volcanic dynamics and improve the forecasting of the volcanic activity. Nevertheless, it can be a useful tool to investigate the surface temperature field of any areas subjected to thermal anomalies, both of natural and anthropic origin.
Land Cover Changes and Their Driving Mechanisms in Central Asia from 2001 to 2017 Supported by Google Earth Engine
Authors: Hu Yunfeng , Hu Yang
Published: March 2019

Limited research has been published on land changes and their driving mechanisms in Central Asia, but this area is an important ecologically sensitive area. Supported by Google Earth Engine (GEE), this study used Landsat satellite imagery and selected the random forest algorithm to perform land classification and obtain the annual land cover datasets of Central Asia from 2001 to 2017. Based on the temporal datasets, the distributions and dynamic trends of land cover were summarized, and the key factors driving land changes were analyzed. The results show that (1) the obtained land datasets are reliable and highly accurate, with an overall accuracy of 0.90 ± 0.01. (2) Grassland and bareland are the two most prominent land cover types, with area proportions of 45.0% and 32.9% in 2017, respectively. Over the past 17 years, bareland has displayed an overall reduction, decreasing by 2.6% overall. Natural vegetation (grassland, forest, and shrubland), cultivated land, water bodies and wetlands have displayed increasing trends at different rates. (3) The amount of precipitation and degree of drought are the driving factors that affect natural vegetation. The changes in cultivated land are mainly affected by precipitation and anthropogenic drivers. The effects of increasing urban populations and expanding industrial development are the factors driving the expansion of urban regions. The advantages and uncertainties arising from the land mapping and change detection method and the complexity of the driving mechanisms are also discussed.
Artificial Intelligence-Assisted Heating Ventilation and Air Conditioning Control and the Unmet Demand for Sensors: Part 1. Problem Formulation and the Hypothesis
Authors: Cheng Chin-Chi , Lee Dasheng
Published: March 2019

In this study, information pertaining to the development of artificial intelligence (AI) technology for improving the performance of heating, ventilation, and air conditioning (HVAC) systems was collected. Among the 18 AI tools developed for HVAC control during the past 20 years, only three functions, including weather forecasting, optimization, and predictive controls, have become mainstream. Based on the presented data, the energy savings of HVAC systems that have AI functionality is less than those equipped with traditional energy management system (EMS) controlling techniques. This is because the existing sensors cannot meet the required demand for AI functionality. The errors of most of the existing sensors are less than 5%. However, most of the prediction errors of AI tools are larger than 7%, except for the weather forecast. The normalized Harris index (NHI) is able to evaluate the energy saving percentages and the maximum saving rations of different kinds of HVAC controls. Based on the NHI, the estimated average energy savings percentage and the maximum saving rations of AI-assisted HVAC control are 14.4% and 44.04%, respectively. Data regarding the hypothesis of AI forecasting or prediction tools having less accuracy forms Part 1 of this series of research.
Microservice-Oriented Platform for Internet of Big Data Analytics: A Proof of Concept
Authors: Li Zheng , Seco Diego , Sánchez Rodríguez Alexis Eloy
Published: March 2019

The ubiquitous Internet of Things (IoT) devices nowadays are generating various and numerous data from everywhere at any time. Since it is not always necessary to centralize and analyze IoT data cumulatively (e.g., the Monte Carlo analytics and Convergence analytics demonstrated in this article), the traditional implementations of big data analytics (BDA) will suffer from unnecessary and expensive data transmissions as a result of the tight coupling between computing resource management and data processing logics. Inspired by software-defined infrastructure (SDI), we propose the “microservice-oriented platform” to break the environmental monolith and further decouple data processing logics from their underlying resource management in order to facilitate BDA implementations in the IoT environment (which we name “IoBDA”). Given predesigned standard microservices with respect to specific data processing logics, the proposed platform is expected to largely reduce the complexity in and relieve inexperienced practices of IoBDA implementations. The potential contributions to the relevant communities include (1) new theories of a microservice-oriented platform on top of SDI and (2) a functional microservice-oriented platform for IoBDA with a group of predesigned microservices.
Comparative Study of Different Methods in Vibration-Based Terrain Classification for Wheeled Robots with Shock Absorbers
Authors: Mei Mingliang , Chang Ji , Li Yuling , Li Zerui , Li Xiaochuan , Lv Wenjun
Published: March 2019

Autonomous robots that operate in the field can enhance their security and efficiency by accurate terrain classification, which can be realized by means of robot-terrain interaction-generated vibration signals. In this paper, we explore the vibration-based terrain classification (VTC), in particular for a wheeled robot with shock absorbers. Because the vibration sensors are usually mounted on the main body of the robot, the vibration signals are dampened significantly, which results in the vibration signals collected on different terrains being more difficult to discriminate. Hence, the existing VTC methods applied to a robot with shock absorbers may degrade. The contributions are two-fold: (1) Several experiments are conducted to exhibit the performance of the existing feature-engineering and feature-learning classification methods; and (2) According to the long short-term memory (LSTM) network, we propose a one-dimensional convolutional LSTM (1DCL)-based VTC method to learn both spatial and temporal characteristics of the dampened vibration signals. The experiment results demonstrate that: (1) The feature-engineering methods, which are efficient in VTC of the robot without shock absorbers, are not so accurate in our project; meanwhile, the feature-learning methods are better choices; and (2) The 1DCL-based VTC method outperforms the conventional methods with an accuracy of 80.18%, which exceeds the second method (LSTM) by 8.23%.
A Fuzzy-Innovation-Based Adaptive Kalman Filter for Enhanced Vehicle Positioning in Dense Urban Environments
Authors: Woo Rinara , Yang Eun-Ju , Seo Dae-Wha
Published: March 2019

In this paper, a fuzzy-innovation based adaptive extended Kalman filter (FI-AKF) is proposed to improve the performance of the GNSS/INS fusion system, which is degraded due to satellite signal cutoff and attenuation and inaccurate modeling in dense urban environments. The information used for sensor fusion is obtained from real-time kinematic (RTK), micro-electro-mechanical system based inertial measumrement unit (MEMS-IMU), and on-board diagnostics (OBD). The fuzzy logic system is proposed to adaptively update the measurement covariance matrix of the RTK according to the position dilution of precision (PDOP), the number of receivable satellites, and the innovation of the extended Kalman filter (EKF). In addition, the driving state of the vehicle is defined as stop, straight run, left/right turn, and the like. To reduce the heading estimation error of the Kalman filter, the estimated heading is corrected according to the driving state. Also, the measurement covariance matrices of IMU and OBD are applied adaptively considering the characteristics of each sensor according to the driving state. In order to analyze the performance of the proposed FI-AKF positioning system in a dense urban environment, a computer simulation is performed. The proposed FI-AKF is compared to the performance of the existing extended Kalman filter and the innovation-based adaptive extended Kalman filter. In addition, we conduct a performance comparison experiment with a commercial positioning system in the field test. Through each experiment, it is confirmed that the proposed FI-AKF system has higher positioning performance than the comparison positioning systems in a dense urban environment.
Estimation of Pedestrian Pose Orientation Using Soft Target Training Based on Teacher–Student Framework
Authors: Heo DuYeong , Nam Jae Yeal , Ko Byoung Chul
Published: March 2019

Semi-supervised learning is known to achieve better generalisation than a model learned solely from labelled data. Therefore, we propose a new method for estimating a pedestrian pose orientation using a soft-target method, which is a type of semi-supervised learning method. Because a convolutional neural network (CNN) based pose orientation estimation requires large numbers of parameters and operations, we apply the teacher–student algorithm to generate a compressed student model with high accuracy and compactness resembling that of the teacher model by combining a deep network with a random forest. After the teacher model is generated using hard target data, the softened outputs (soft-target data) of the teacher model are used for training the student model. Moreover, the orientation of the pedestrian has specific shape patterns, and a wavelet transform is applied to the input image as a pre-processing step owing to its good spatial frequency localisation property and the ability to preserve both the spatial information and gradient information of an image. For a benchmark dataset considering real driving situations based on a single camera, we used the TUD and KITTI datasets. We applied the proposed algorithm to various driving images in the datasets, and the results indicate that its classification performance with regard to the pose orientation is better than that of other state-of-the-art methods based on a CNN. In addition, the computational speed of the proposed student model is faster than that of other deep CNNs owing to the shorter model structure with a smaller number of parameters.
An Integrated Design Framework for Safety Interventions on Existing Urban Roads—Development and Case Study Application
Authors: Colonna Pasquale , Intini Paolo , Berloco Nicola , Fedele Veronica , Masi Giuseppe , Ranieri Vittorio
Published: March 2019

The need for improving urban road safety, livability, and sustainability is evident. Quantitative estimates and qualitative methods/strategies can be used by road safety practitioners to design safety interventions. This study proposes a flexible integrated design framework for safety interventions on existing urban road segments and intersections that integrates quantitative and qualitative methods. The proposed design framework is divided into four stages of the safety management process: End of Network Screening, Diagnosis, Selection of Countermeasures, and Economic Assessment. Pilot applications of the proposed method were performed on existing roads of the urban road network of the Municipality of Bari, Italy. Results from the application were useful to highlight some possible problems in the different stages of the design process. In particular, the discussed problems include a lack of crash and traffic data, difficulties with defining the road functional classifications, including rural-to-urban transitions, a lack of local inspection procedures, the recurrent problems from diagnosis, difficulties regarding the safety assessment of cycling infrastructures and sight distances, the criteria for grouping countermeasures into sets, and the choice of appropriate predictive methods. In response, appropriate solutions to the highlighted problems were presented. The usefulness of the proposed method for both practitioners and researchers was shown.
Selection of Manufacturing Enterprise Innovation Design Project Based on Consumer’s Green Preferences
Authors: Yang Jie , Su Jiafu , Song Lijun
Published: March 2019

For enterprise, how to quickly realize the selection of green innovative design projects has become a key issue for improving innovation performance. Based on an analysis of enterprise product innovation and customer green preferences, an indicator set for innovation performance in enterprise was established. Considering the fuzziness of the correlation between indicators for innovation performance in enterprise and consumer’s green preferences, a fuzzy clustering method was used to identify the internal relations among the indicators for innovation performance with green preferences of customers. Then a wavelet neural network was used to select the innovation design project for various green preferences of customers. Finally, a case study was proposed to verify the feasibility and effectiveness of the method. This work can help the enterprise to develop green design, products, and serve uniformly, which can effectively shorten green product development cycles, reduce cost, and improve enterprise innovation performance greatly.
Analytical Study of the Head-On Collision Process between Hydroelastic Solitary Waves in the Presence of a Uniform Current
Authors: Bhatti Muhammad Mubashir , Lu Dong Qiang
Published: March 2019

The present study discusses an analytical simulation of the head-on collision between a pair of hydroelastic solitary waves propagating in the opposite directions in the presence of a uniform current. An infinite thin elastic plate is floating on the surface of water. The mathematical modeling of the thin elastic plate is based on the Euler–Bernoulli beam model. The resulting kinematic and dynamic boundary conditions are highly nonlinear, which are solved analytically with the help of a singular perturbation method. The Poincaré–Lighthill–Kuo method is applied to obtain the solution of the nonlinear partial differential equations. The resulting solutions are presented separately for the left- and right-going waves. The behavior of all the emerging parameters are presented mathematically and discussed graphically for the phase shift, maximum run-up amplitude, distortion profile, wave speed, and solitary wave profile. It is found that the presence of a current strongly affects the wavelength and wave speed of both solitary waves. A graphical comparison with pure-gravity waves is also presented as a particular case of our study.
Optimizing MSE for Clustering with Balanced Size Constraints
Authors: Tang Wei , Yang Yang , Zeng Lanling , Zhan Yongzhao
Published: March 2019

Clustering is to group data so that the observations in the same group are more similar to each other than to those in other groups. k-means is a popular clustering algorithm in data mining. Its objective is to optimize the mean squared error (MSE). The traditional k-means algorithm is not suitable for applications where the sizes of clusters need to be balanced. Given n observations, our objective is to optimize the MSE under the constraint that the observations need to be evenly divided into k clusters. In this paper, we propose an iterative method for the task of clustering with balanced size constraints. Each iteration can be split into two steps, namely an assignment step and an update step. In the assignment step, the data are evenly assigned to each cluster. The balanced assignment task here is formulated as an integer linear program (ILP), and we prove that the constraint matrix of this ILP is totally unimodular. Thus the ILP is relaxed as a linear program (LP) which can be efficiently solved with the simplex algorithm. In the update step, the new centers are updated as the centroids of the observations in the clusters. Assuming that there are n observations and the algorithm needs m iterations to converge, we show that the average time complexity of the proposed algorithm is O ( m n 1.65 ) – O ( m n 1.70 ) . Experimental results indicate that, comparing with state-of-the-art methods, the proposed algorithm is efficient in deriving more accurate clustering.
Mycotoxins and Related Fungi in Italian Paddy Rice During the Growing Season and Storage
Authors: Bertuzzi Terenzio , Romani Marco , Rastelli Silvia , Giorni Paola
Published: March 2019

Mycotoxigenic fungi and relative mycotoxins contamination were monitored in Italian paddy rice samples both in field during the growing season and the first five months of storage. Three experimental fields, nine rice varieties and three sowing densities were considered; then, different lots of paddy rice were stored in warehouses at different temperature regimes. Fusarium spp. and Aspergillus spp. were found to be the fungi most likely to produce mycotoxins throughout the growing season. In particular, A. flavus and A. niger were found only rarely both in field and in post-harvest, while A. versicolor was always present although in low concentrations. Penicillium spp. strains were isolated sporadically and were found to be irrelevant in Italian rice fungal contamination. Sterigmatocystin (STC) was the main mycotoxin found in Italian rice, while aflatoxin (AFB1), deoxynivalenol (DON) and ochratoxin A (OTA) were rarely detected. Contamination generally increased from post-flowering to ripening; considering rice varieties, significant differences (p ≤ 0.01) were found in fungal contamination and STC production; no differences were observed between sowing densities. During storage, an increase in STC content was observed in higher temperature regimes, while all the other considered mycotoxins remained unchanged. These results indicated that contamination by STC, an emerging mycotoxin not legislatively regulated by the European Union, can be relevant in rice.
Metabolomic Insights into Human Arboviral Infections: Dengue, Chikungunya, and Zika Viruses
Authors: Byers Nathaniel M. , Fleshman Amy C. , Perera Rushika , Molins Claudia R.
Published: March 2019

The global burden of arboviral diseases and the limited success in controlling them calls for innovative methods to understand arbovirus infections. Metabolomics has been applied to detect alterations in host physiology during infection. This approach relies on mass spectrometry or nuclear magnetic resonance spectroscopy to evaluate how perturbations in biological systems alter metabolic pathways, allowing for differentiation of closely related conditions. Because viruses heavily depend on host resources and pathways, they present unique challenges for characterizing metabolic changes. Here, we review the literature on metabolomics of arboviruses and focus on the interpretation of identified molecular features. Metabolomics has revealed biomarkers that differentiate disease states and outcomes, and has shown similarities in metabolic alterations caused by different viruses (e.g., lipid metabolism). Researchers investigating such metabolomic alterations aim to better understand host–virus dynamics, identify diagnostically useful molecular features, discern perturbed pathways for therapeutics, and guide further biochemical research. This review focuses on lessons derived from metabolomics studies on samples from arbovirus-infected humans.
Real-Time Dynamic Hydraulic Model of Water Distribution Networks
Authors: Abu-Mahfouz Adnan M. , Hamam Yskandar , Page Philip R. , Adedeji Kazeem B. , Anele Amos O. , Todini Ezio
Published: March 2019

The impact of climate change and increasing urbanisation throughout the world has forced water utility managers to increase the efficiency of water resources. Reduction of real (or physical) water losses plays a crucial role in improving the efficiency of water supply systems. Considering these challenges, it will not be enough to rely only on traditional approaches to solve the problem of water losses. Therefore, more advanced techniques need to be developed and utilized. Recently, a framework for a real-time dynamic hydraulic model for potable water loss reduction was proposed. This paper focuses mainly on the three major components of the proposed real-time dynamic hydraulic model framework for potable water loss reduction, which have been developed recently. These are background leakage detection, pressure management, and water demand forecasting. A background leakage detection algorithm was proposed which, amongst others, permits the localisation of potential critical nodes or pipes with higher leakage flow in the network where such pressure management could be performed. More so, new controllers (algorithms) which perform pressure management by accurately setting the pressure, using either a pressure control valve or variable speed pump, have been constructed. In addition, background leakage flow is greatly affected by demand variations, a water demand forecasting model is constructed with the aim of annexing the demand variation for multi-period leakage analysis. Thus, a short-term water demand forecast utilising the Model Conditional Processor was constructed to forecast the following hour demand and the associated predictive uncertainty. Although each of these components have been tested independently, future work is ongoing for merging these components and integration within the dynamic hydraulic model framework.
Correlation Analysis Between Groundwater Decline Trend and Human-Induced Factors in Bashang Region
Authors: Hao Zhen , Zhao Hesong , Zhang Chi , Zhou Huicheng , Zhao Hongli , Wang Hao
Published: March 2019

In Northern China, many regions and cities are located in semi-arid regions, and groundwater is even the only source of water to support human survival and social development. Affected by human activities, the Bashang (BS) region (including Zhangjiakou City and part of Xilin Gol League) have showed a significant decline in groundwater levels in recent years. However, in the BS region, the causes for the decline in groundwater level were not clear. In this study, we used time series of multi-source data Moderate Resolution Imaging Spectroradiometer (MODIS), Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) to analyze vegetation and groundwater changes based on linear regression models. The variation trends of NDVI (Normalized Difference Vegetation Index, derived from MODIS) and GWSA (groundwater storage anomaly, derived from GRACE and GLDAS) indicated the increasingly better vegetation in the agriculture planting areas, partially degraded vegetation in the grassland, and the declining groundwater level in the whole study region. In order to assess the impact of human-induced factors on vegetation and groundwater, the R U E s e a s o n a l calculation model was proposed based on RUE (rain use efficiency) in this study. The R U E s e a s o n a l calculation results showed that human-induced factors promoted the growth of vegetation in agricultural areas and accelerated the consumption of groundwater. In addition, we also obtained temporal and spatial distributions of human activities-affected regions. The area affected by human-induced factors in the south-central study area increased, which accelerated the decline in groundwater levels. From bulletin data, we found that the increasing tourists and vegetable production are respectively the most important factors for the increased consumption of urban water and agricultural water. Based on multi-source data, the influences of various human-induced factors on the ecological environment were explored and the area affected by human-induced factors was estimated. The results provide the valuable guidance for water resource management departments. In the BS region, it is necessary to regulate agricultural water use and strengthen residential water management.
Burden and Correlates of Hospital Readmissions among U.S. Peritoneal Dialysis Patients
Authors: Sahlie Abyalew , Jaar Bernard G. , Paez Lilian Galarza , Masud Tahsin , Lea Janice P. , Burkart John M. , Plantinga Laura C.
Published: March 2019

Background

Hospital readmissions are common among in- center hemodialysis patients, but little is known about read-missions among peritoneal dialysis (PD) patients. Using national administrative data, we aimed to examine the burden and correlates of hospital readmissions among U.S. PD patients.

Methods

Among 10,505 adult U.S. PD patients with an index admission (first admission after 120 days on dialysis) between 31 January 2011 and 30 November 2014, readmissions were defined as new hospital admissions within 30 days of index discharge. Multivariable logistic regression was used to obtain adjusted odds ratios (ORs) for readmission.

Results

Overall, 26.8% of index admissions were followed by a readmission. Readmitted patients were more likely to have congestive heart failure (31.0% vs 25.4%; p < 0.001) and peripheral arterial disease (11.6% vs 8.6%; p < 0.001) and had longer index admission length of stay (median = 4 vs 3 days; p < 0.001) than those who were not; age, sex, and race did not differ by readmission status. After adjustment for patient and index admission characteristics, longer length of stay (≥ 4 vs < 4 days, OR = 1.48, 95% confidence interval [CI] 1.35 – 1.62), peripheral arterial disease (OR = 1.31, 95% CI 1.16 – 1.57), congestive heart failure (OR = 1.25, 95% CI 1.13 – 1.39), and ischemic heart disease (OR = 1.12, 95% CI 1.01 – 1.24) were associated with higher likelihood of readmission; index admission due to peritonitis vs other causes was associated with lower likelihood of readmission (OR = 0.80, 95% CI 0.70 – 0.92).

Conclusions

Our results suggest that, particularly in the absence of a PD-related cause of hospitalization such as peritonitis, PD patients may be at high risk for readmission and may benefit from closer post-discharge monitoring.
Peritoneal Dialysis Cuff-Shaving—A Salvage Therapy for Refractory Exit-Site Infections
Authors: Meng Catarina , Beco Ana , Oliveira Ana , Pereira Luciano , Pestana Manuel
Published: March 2019

Introduction

Cuff-shaving has been described as a salvage technique for refractory exit-site infections, with conflicting data regarding infection and catheter outcomes. We describe our experience with cuff-shaving as a rescue therapy for exit-site infections unresponsive to systemic therapy.

Methods

We retrospectively reviewed patients who underwent cuff-shaving between January 2012 and June 2017. Refractory exit-site infection was defined as purulent discharge from the exit site with no clinical response after 3 weeks of systemic antibiotic treatment.

Results

Fifty-three cuff-shavings were included, mean age was 53.4 ± 13.4 years, 26 patients were male. Median dialysis vintage was 29 months (interquartile range [IQR] 14.3 – 38), and 39 (73.6%) were on continuous ambulatory peritoneal dialysis (CAPD). The exit-site infection rate before cuff-shaving was 1.12 episodes per patient-year and the median time from infection to shaving was 52 days (IQR 35 – 76). The most frequent agents were Staphylococcus aureus (34%), Corynebacterium spp. (17%) and Pseudomonas aeruginosa (15%). Median follow-up was 9 months (IQR 1 – 18.5), during which time 35 catheters were removed, 5 due to non-infectious reasons. Using the Kaplan-Meier survival analysis, median catheter survival was 24 months (95% confidence interval [CI] 4.17 – 43.83). At 12 months, the probability of catheter survival was 54% and was not statistically different between gram-positive and gram-negative agents, although it was significantly shorter for fungal agents.

Conclusion

Cuff-shaving is a feasible rescue therapy to treat refractory exit-site infections. In our experience, it allowed resolution of infections in a significant proportion of cases, except for fungal agents, and therefore extended catheter survival time, besides being associated with a small rate of complications.
Computer Simulations of Continuous Flow Peritoneal Dialysis Using the 3-Pore Model—A First Experience
Authors: Öberg Carl M. , Martuseviciene Giedre
Published: March 2019

Background

Continuous flow peritoneal dialysis (CFPD) is performed using a continuous flux of dialysis fluid via double or dual-lumen PD catheters, allowing a higher dialysate flow rate (DFR) than conventional treatments. While small clinical studies have revealed greatly improved clearances using CFPD, the inability to predict ultrafiltration (UF) may confer a risk of potentially harmful overfill. Here we performed physiological studies of CFPD in silico using the extended 3-pore model.

Method

A 9-h CFPD session was simulated for: slow (dialysate to plasma creatinine [D/P crea] < 0.6), fast (D/P crea > 0.8) and average (0.6 < D/P crea < 0.8) transporters using 1.36%, 2.27%, or 3.86% glucose solutions. To avoid overfill, we applied a practical equation, based on the principle of mass-balance, to predict the UF rate during CFPD treatment.

Results

Increasing DFR > 100 mL/min evoked substantial increments in small- and middle-molecule clearances, being 2 - 5 times higher compared with a 4-h continuous ambulatory PD (CAPD) exchange, with improvements typically being smaller for average and slow transporters. Improved UF rates, exceeding 10 mL/min, were achieved for all transport types. The β2-microglobulin clearance was strongly dependent on the UF rate and increased between 60% and 130% as a function of DFR. Lastly, we tested novel intermittent-continuous regimes as an alternative strategy to prevent overfill, being effective for 1.36% and 2.27%, but not for 3.86% glucose.

Conclusion

While we find substantial increments in solute and water clearance with CFPD, previous studies have shown similar improvements using high-volume tidal automated PD (APD). Lastly, the current in silico results need confirmation by studies in vivo.
Commercial polycarbonate track-etched membranes as substrates for low-cost optical sensors
Authors: Martínez-Pérez Paula , García-Rupérez Jaime
Published: March 2019

Porous materials have become one of the best options for the development of optical sensors, since they maximize the interaction between the optical field and the target substances, which boosts the sensitivity. In this work, we propose the use of a readily available mesoporous material for the development of such sensors: commercial polycarbonate track-etched membranes. In order to demonstrate their utility for this purpose, we firstly characterized their optical response in the near-infrared range. This response is an interference fringe pattern, characteristic of a Fabry–Pérot interferometer, which is an optical device typically used for sensing purposes. Afterwards, several refractive index sensing experiments were performed by placing different concentrations of ethanol solution on the polycarbonate track-etched membranes. As a result, a sensitivity value of around 56 nm/RIU was obtained and the reusability of the substrate was demonstrated. These results pave the way for the development of optical porous sensors with such easily available mesoporous material.
CHLORIDE PENETRATION INTO MORTAR FOR NON-DESTRUCTIVE DETERMINATION OF THE CHLORIDE BINDING ISOTHERM/CHLORIDO SKVARBA Į SKIEDIKLĮ KAIP NEARDOMASIS BŪDAS CHLORIDO RIŠAMAJAI IZOTERMAI NUSTATYTI
Authors: Bigas Jean-Philippe
Published: March 2019

Chlorido įsiskverbimo į betono struktūrą koeficientą galima būtų nustatyti išmatavus efektyviosios difuzijos koeficientą nustačius nelinijinį chlorido ir betono rišimąsi. Siūlomas naujas būdas rišimosi procesui modeliuoti—Freundlicho izoterma, apskaičiavus jos lygtį iš kelių tradicinių difuzijos bandymų pastoviosios būklės sąlygomis.

Siūlomo būdo pranašumas (palyginti su klasikiniais bandymų metodais, kai rišimosi izotermos gaunamos iš trupintų bandinių) yra tas, kad taikoma nelinijinio rišimosi izotermos lygtis betono mikrostruktūrai natūraliomis eksploatacijos sąlygomis. Šiuo atveju galima studijuoti mikrostruktūros poveikį chlorido jonų rišimuisi.
CONSOLIDATION OF DISTURBED AND UNDISTURBED CLAY AND DIFFERENTIAL SETTLEMENT OF BUILDINGS
Authors: Alikonis Antanas
Published: March 2019

Differential settlement of foundations stimulates the development of cracks in structures. However different rate of settlements could be the reason of cracks. The highest rate of settlement takes place during the consolidation period. Theoretical calculations and experimental data showed that rate of settlement of disturbed soil is higher in comparison with undisturbed soil. During the loading of undisturbed soil with structural links displacement of particles and pore pressure dissipation are slower. Pore pressure dissipation begins only after the structural links are broken, ie after the additional stress becomes higher than preconsolidation pressure. The process of disintegration of structural links is slow, therefore the rate of consolidation settlement is also slow. If there are zones of disturbed clay within the layout of building, differential settlement of building can occur. Parameters which are necessary for estimation of the primary consolidation rate of disturbed soil could be calculated using compression curve of the same soil drawn in the semi-logarithmic scale. According to the results of investigations the method described above could be used to predict the rate of primary consolidation of foundations.
RISK ANALYSIS IN THE INVESTMENTS OF CONSTRUCTION PROJECTS/RIZIKOS ANALIZĖS REIKŠMĖ STATYBOS INVESTICINIAMS PROJEKTAMS
Authors: Tamošiūnienė Rima
Published: March 2019

Lithuanian economy transformation into a market economy extremely increased the risk of enterprises. Transition from a producer market to a consumer market caused the technological innovations in construction business. It needs long-term investments. So the management of such investments risk is a problem of today.

The paper deals with indentifying conceptual problems of risk and uncertainty definition as well as indicators for the quantitative risk management.

Some aspects of the application of the risk management ideology which is thought as risk analysis and risk reduction are discussed. Risk analysis includes methods such as sensitivity analysis, breakeven point analysis, mathematical programming methods, scenario analysis, Monte-Carlo technique etc.

There are many types of risk in business. Risks can be classified as external unforeseeable risks, external foreseeable (but not determined) risks, operating risks, technical risks, legal risks etc. The first step in risk management is the risk analysis, then follows the application of risk reduction methods.
THE ESTIMATION PROBLEMS OF THE FIRE HAZARD FOR VERTICALLY ORIENTED BUILDING PRODUCTS/VERTIKALIAI ORIENTUOTŲ STATYBINIŲ GAMINIŲ GAISRINIO PAVOJINGUMO ĮVERTINIMO PROBLEMOS
Authors: Nyderis Albertas
Published: March 2019

The Directive of new approach 89/106/EEC, which was prepared by Directorate General of the European Commission (DG III), defines the guidelines for development of fire protection in building construction. Six main directions for development of fire protection are defined in this Directive as well.

Solid materials are most numerous among building products. Therefore a brief analysis of combustion process of these materials is presented in this article. F.Williams developed the theoretical principles of combustion. Phase transitions in the zone of combustion are analyzed in the theory. Formulas 1–4 describe this process. The process of combustion of solid materials is heterogeneous; therefore the model of pyrolysis is presented by 5 formulas.

An intricate energy exchange takes place in real fires. The heat is being transferred in different ways. The most acceptable description of heat transfer is by means of radiation. Description of this process is presented in formulas 6–7. The heat transfer by means of radiation can be modelled and used for environment testing.

The combustibility of building products can be examined by means of reaction of fire tests. In recent years tests for different building products were carried out according to ISO 5657 test methodology in the Fire Research Centre. Test results indicate that the time to sustained surface ignition for building products is inversely proportional to heat flux. This logarithmic dependence is presented in 8 formulas. Establishment of parameters of this logarithmic flow for different building products can prove this. This work was carried out during the process of verification of this hypothesis.

Analysis of fire testing practice of vertically oriented building products in different countries shows that harmonized fire test methods for these products do not exist. Most of these test methods are based on presumption that the flame spread is possible only inside the building not considering the behaviour of facade in fire.

The main idea of fire test method for element of vertically oriented building construction together with the principal scheme of test equipment are presented in the article as well.

Further development of this idea leads to five questions, which should be answered to solve the problem. After the completion of this task and analysis of test results, all the information is to be submitted for further consideration.
STALACTITIZATION OF CONCRETE STRUCTURES, THIN COATING FORMATION AND ITS REDUCTION/BETONINIŲ KONSTRUKCIJŲ STALAKTITIZACIJA, APNAŠŲ SUSIDARYMAS IR JŲ MAŽINIMAS
Authors: Kazragis Loreta , Valaitytė Halina
Published: March 2019

Concrete and reinforced concrete construction of buildings and bridges, concrete slabs for laying streets, concrete tiles for laying pavements and squares are often covered with thin coating reminding of stalactites or white-grey flows. This phenomenon can be called stalactitization of concrete. It does not just worsen the decorative properties of concrete and reinforced concrete, but also weakens the mechanical strength of these materials.

We discuss the reasons of stalactitization of concrete and reinforced concrete constructions and articles and recommend means to weaken this process.

The processes of concrete structure stalactitization and formation of thin coating can be delayed in the following ways:

Using a filler in production, which has calcite and limestone as little as possible, and controlling their amount by methods of chemical analysis.

For CaO (0,5%), present in Portland cement, and for forming Ca(OH)2 in concrete neutralization substances containing SiO2 and SiO2 nH2O can be used but, to prevent alkaline corrosion of concrete, they can be applied only when Portland cement contains very little Na2O and K2O.

If there is a possibility, do not use passivated Portland cement containing FeSO4 and A1(SO4)3.

Avoid an excess of water when making concrete mixtures.

Coloured or other concrete articles should be stored under a roof or at least be covered.
THE METHOD NNM AND ITS APPLICATION IN A SOZOECONOMIC ANALYSIS OF THE PROCESS REALIZATION WITHIN A CYCLE OF A BUILDING STRUCTURE/SKAITMENINIO TINKLO MODELIAVIMO (STM) METODAS IR JO TAIKYMAS SOCOEKONOMINEI STATYBOS OBJEKTO REALIZAYIMO ANALIZEI
Authors: Więckowski Andrzej
Published: March 2019

Metodas, vadinamas STM (angl. NNM), taikomas analizuojant, planuojant ir kontroliuojant sudėtingus, tarpusavyje susijusius procesus, vykstantys besikeičiančioms sąlygoms, per daugelį metų įgyja skirtingų ypatybių. STM tinklas turi dviejų punktų struktūrą. Viršūnės logika, sudaryta biologinio neurono pavyzdžiu, taikoma tinklui, kuris visiškai skiriasi nuo dirbtinių neuronų tinklų. Ji leido analizuoti aprašymą ir lengvai tirti bei sudaryti tiek deterministinius modelius (pvz., CPM ar PERT), tiek GAN klasės tikimybinius modelius, o drauge ir sprendžiamuosius modelius. Be to, ji sudaro galimybę individualiai pateikti priėmimo, aktyvacijos ir emisijos sąlygas. Ji tinka ir pasirinktiems briaunų bei trajektorijų pavyzdžiams.

Analizė apima visus procesus, kurie sudaro organizuotą veiksmų (ciklų) seką, pradedant statybos objektu, baigiant pasirengimu, eksploatacija bei priežiūra. Tai procesai, prasidėję nuo pirmosios idėjos apie objektą, vėliau perėję į planavimą, pasirengimą ir statybą ilgą eksploataciją, remontus ir užsibaigę veiklos nutraukimu.

Socoekonominė analizė atsižvelgia į investicijų naudingumą B I (δT), aplinkosauginius privalumus B e (δT) ir neįvertintas išlaidas aplinkosaugai PVe.
PATENT COOPERATIVE PATTERNS AND DEVELOPMENT TRENDS OF CHINESE CONSTRUCTION ENTERPRISES: A NETWORK ANALYSIS
Authors: Zhong Botao , Hei Yongjian , Li Heng , Rose Timothy , Luo Hanbin
Published: March 2019

Despite the rapid development of Chinese construction industry, there has been little research effort directed towards exploring patent cooperative patterns and evolution trends of construction enterprises, especially from the perspective of the patent development network. This paper extracts implicit collaborative information and introduces Social Network Analysis (SNA) method to conduct the patentometric analysis based on patent data from the “Top 500 Chinese Construction Enterprises” sourced from PatSnap database. The enterprise-enterprise networks and enterprise-university networks are analyzed quantitatively. The results reveal that: 1) there is a rising trend in the number of patents and patentees; 2) state-owned enterprises play a dominant role in patent development; 3) most of patents are classified as International Patent Classification E04G21; 4) the cooperative relationships are mainly within enterprises and their subsidiaries; 5) when enterprises choose to cooperate with universities, in addition to professional qualification, geographical factors should also be considered. Finally, the development and patent evolution trends are discussed. Some useful suggestions are proposed. The contribution lies in: (a) providing a visualization of the implicit collaboration information of patents in Chinese construction enterprises; (b) revealing cooperative patterns of construction enterprises on patents; and (c) providing enterprises some useful suggestions for patent cooperation.
SOLVING CONSTRUCTION PROJECT SELECTION PROBLEM BY A NEW UNCERTAIN WEIGHTING AND RANKING BASED ON COMPROMISE SOLUTION WITH LINEAR ASSIGNMENT APPROACH
Authors: Davoudabadi Reza , Meysam Mousavi Seyed , Šaparauskas Jonas , Gitinavard Hossein
Published: March 2019

Selecting a suitable construction project is a significant issue for contractors to decrease their costs. In real cases, the imprecise and uncertain information lead to decisions made based on vagueness. Fuzzy sets theory could help decision makers (DMs) to address incomplete information. However, this article develops a new integrated multi-criteria group decision-making model based on compromise solution and linear assignment approaches with interval-valued intuitionistic fuzzy sets (IVIFSs). IVIFSs by presenting a membership and non-membership degree for each candidate based on appraisement criteria could decrease the vagueness of selection decisions. The proposed algorithm involves a new decision process under uncertain conditions to determine the importance of criteria and DMs, separately. In this regard, no subjective or additional information is needed for this process; only the input information required is an alternative assessment matric. In this approach, weights of criteria and DMs are specified based on novel indexes to increase the reliability of obtained results. In this respect, the criteria’ weights are computed regarding entropy concepts. The basis for calculating the weight of each DM is the distance between each DM and an average of the DMs’ community. Furthermore, the linear assignment model is extended to rank the candidates. A case study about the construction project selection problem (CPSP) is illustrated to indicate the application of proposed model.
Observations of Red Giants with Suspected Massive Companions
Authors: Makarov Valeri V. , Tokovinin Andrei
Published: March 2019

Motivated by the existence of binary systems where a stellar-mass black hole is bound to a normal star, we selected four red giants with large radial velocity (RV) variation from the survey of Space Interferometry Mission (SIM) grid stars and monitored their RVs for several months. None turned out to contain a massive companion above 2.5 solar masses. The red giant TYC 9299-1080-1 with a large RV and a large proper motion is a single-lined spectroscopic binary with a period of 81 days. It is an extreme halo object moving at 350 km s−1 almost directly toward the Galactic center. HD 206092 is a double-lined binary with a short period of 4.37 days. It belongs to the rare class of active RS CVn-type binaries with evolved primary components, apparently undergoing mass transfer. The X-ray luminosity of HD 206092 is about twice as high as the most luminous coronal X-ray emitters observed by ROSAT, including II Peg and the prototype star RS CVn. HD 318347 has a variable double-peaked emission-line spectrum (not a giant), while HD 324668 has a constant RV. Despite the overall good quality of the SIM survey data confirmed by a comparison with Gaia Data Release 2 (DR2) mean RVs, the few large RV variations are explained, mostly, by erroneous data. We discuss the significance of the non-detection of massive companions in the SIM grid sample and the associated work.