bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary Approaches for Japanese Patients with Diabetes: A Systematic Review
Authors: Yamada Satoru , Kabeya Yusuke , Noto Hiroshi
Published: August 2018

This study aimed to elucidate the effect of an energy restricted and carbohydrate restricted diet on the management of Japanese diabetes patients. Several databases including MEDLINE, EMBASE, and the Japan Medical Abstracts Society were searched for relevant articles published prior to June 2017. The articles identified were systematically reviewed. We identified 286 articles on an energy restricted diet, assessed seven and included two studies in our review. On a carbohydrate restricted diet, 75 articles were extracted, seven articles assessed and three included in the review, of which two were the studies that were selected for the energy restricted diet group, since they compared energy restricted diets with carbohydrate restricted diets. All selected studies were on Japanese patients with type 2 diabetes. No studies for type 1 diabetes were found in our search. Two randomized controlled trials on an energy restricted diet were also included in the three studies for a carbohydrate restricted diet. All the three randomized controlled trials showed better glucose management with the carbohydrate restricted diet. Our study revealed that there is very little evidence on diets, particularly in Japanese patients with diabetes, and that the energy restricted diet, which has been recommended by the Japan Diabetes Society in the sole dietary management approach, is not supported by any scientific evidence. Our findings suggest that the carbohydrate restricted diet, but not the energy restricted diet, might have short term benefits for the management of diabetes in Japanese patients. However, since our analysis was based on a limited number of small randomized controlled trials, large scale and/or long term trials examining the dietary approaches in these patients are needed to confirm our findings.
Soybean- and Lupin-Derived Peptides Inhibit DPP-IV Activity on In Situ Human Intestinal Caco-2 Cells and Ex Vivo Human Serum
Authors: Lammi Carmen , Bollati Carlotta , Ferruzza Simonetta , Ranaldi Giulia , Sambuy Yula , Arnoldi Anna
Published: August 2018

Recent investigations have focused on food-derived peptides as novel natural inhibitors of dipeptidyl peptidase IV (DPP-IV), a new target for diabetes. This study aimed to optimize fast, sensitive, and cost-effective DPP-IV assays in situ on human intestinal Caco-2 cells and ex vivo on human serum. Both assays were applied to investigate the inhibitory activity of soy and lupin peptides. The best conditions for in situ DPP-IV activity in Caco-2 cells were obtained using 2-day cells and 50 µM Gly-Pro-AMC. Sitagliptin, used as reference inhibitor, showed a dose-dependent response with a 50% inhibition concentration (IC50) of 0.6 µM. A lower IC50 (0.2 µM) was obtained for sitagliptin on human serum incubated with the substrate for 24 h. Both assays were applied to assess the activity of Lup1 (LTFPGSAED) and Soy1 (IAVPTGVA) on DPP-IV. Lup1 and Soy1 inhibited DPP-IV in situ, with IC50 values of of 207.5 and 223.2 µM, respectively, and maintained their inhibitory activity ex vivo on circulating DPP-IV with a slightly lower potency. These assays can be used to characterize the DPP-IV inhibitory activity of food-derived molecules more accurately than in vitro biochemical tests. This combined approach also considers their effects on the circulating form of DPP-IV, correlated to metabolic diseases.
Influence of the Cross-Link Density on the Rate of Crystallization of Poly(ε-Caprolactone)
Authors: Sedov Igor , Magsumov Timur , Abdullin Albert , Yarko Egor , Mukhametzyanov Timur , Klimovitsky Alexander , Schick Christoph
Published: August 2018

Cross-linked poly(ε-caprolactone) (PCL) is a smart biocompatible polymer exhibiting two-way shape memory effect. PCL samples with different cross-link density were synthesized by heating the polymer with various amounts of radical initiator benzoyl peroxide (BPO). Non-isothermal crystallization kinetics was characterized by means of conventional differential scanning calorimetry (DSC) and fast scanning calorimetry (FSC). The latter technique was used to obtain the dependence of the degree of crystallinity on the preceding cooling rate by following the enthalpies of melting for each sample. It is shown that the cooling rate required to keep the cooled sample amorphous decreases with increasing cross-link density, i.e., crystallization process slows down monotonically. Covalent bonds between polymer chains impede the crystallization process. Consequently, FSC can be used as a rather quick and low sample consuming method to estimate the degree of cross-linking of PCL samples.
Nonlinear Material Model for Quasi-Unidirectional Woven Composite Accounting for Viscoelastic, Viscous Deformation, and Stiffness Reduction
Authors: Zhai Zhanyu , Jiang Bingyan , Drummer Dietmar
Published: August 2018

To clarify the individual contribution of viscoelastic and viscous deformation to the global nonlinear response of composites, multilevel cyclic loading-unloading recovery tensile tests were carried out. The experimental results show that there is a linear relationship between the viscous strain and viscoelastic strain of composites, regardless of the off-axis angle or loading stress level. On the basis of experimental results, a coupled damage-plasticity constitutive model was proposed. In this model, the plasticity theory was adopted to assess the evolution of viscous strains. The viscoelastic strain was represented as a linear function of viscous strains. Moreover, the Weibull function of the effective stress was introduced to evaluate the damage variables in terms of stiffness reduction. The tensile stress-strain curves, predicted by the proposed model, showed a good agreement with experimental results.
Preparation and Identification of Optimal Synthesis Conditions for a Novel Alkaline Anion-Exchange Membrane
Authors: Marcos-Madrazo Aitor , Casado-Coterillo Clara , García-Cruz Leticia , Iniesta Jesús , Simonelli Laura , Sebastián Víctor , Encabo-Berzosa María del Mar , Arruebo Manuel , Irabien Ángel
Published: August 2018

The physicochemical and mechanical properties of new alkaline anion-exchange membranes (AAEMs) based on chitosan (CS) and poly(vinyl alcohol) (PVA) polymers doped with unsupported copper nanoparticles (NPs) and copper exchanged over different porous materials were investigated regarding ion-exchange capacity (IEC), OH− conductivity, water uptake (WU), water vapor permeability (WVP), and thermal and mechanical resistance. The influence of the type of filler included in different morphologies and filler loading has been explored using copper exchanged materials such as the layered porous titanosilicate AM-4, layered stannosilicate UZAR-S3, and zeolites Y, MOR, and BEA. Compared to commercially available anion-exchange membranes, the best performing membranes in terms of WU, IEC, OH− conductivity and WVP in this study were those containing 10 wt % of Cu-AM-4 and Cu-UZAR-S3, although 10 wt % Cu-MOR provided better mechanical strength at close values of WVP and anion conductivity. It was also observed that when Cu was exchanged in a porous silicate matrix, its oxidation state was lower than when embedded as unsupported metal NPs. In addition, the statistical analysis of variance determined that the electrochemical properties of the membranes were noticeably affected by both the type and filler loading, and influenced also by the copper oxidation state and content in the membrane, but their hydrophilic properties were more affected by the polymers. The largest significant effects were noticed on the water sorption and transport properties, which gives scope for the design of AAEMs for electrochemical and water treatment applications.
Preparation and Characterization of Polyaluminum Titanium Silicate and its Performance in the Treatment of Low-Turbidity Water
Authors: Liao Lina , Zhang Peng
Published: August 2018

Using conventional coagulant, low turbidity water is difficult to achieve standard. This research uses aluminum chloride, titanium tetrachloride, and sodium silicate as raw materials for the preparation of polyaluminum titanium silicate chloride (PATC). PATC is used to treat low turbidity. The synthetic PATC showed the best coagulating effect in treated water under the following experimental conditions: Reaction temperature of 50 °C, and n(Ti)/n(Al), n(-OH)/n(Ti+Al), and n(Si)/n(Ti+Al) were 0.3, 0.2, and 1.0, respectively. The species distribution and the transformation of PATC showed that the interaction between titanium tetrachloride, sodium silicate, and the hydrolysate of Al influenced the morphology distribution of Al. Temperature and -OH greatly affected the distribution of Alb in PATC. The analysis of infrared spectra and X-ray diffraction indicated that both titanium tetrachloride and sodium silicate had complex chemical reactions with aluminum chloride. Si-O-Ti and Si-O-Al produced by the reaction affected the PATC treatment of low-turbidity water. Scanning electron microscopy showed, that compared with polyaluminum chloride(PAC), the PATC cluster was more compact, showed greater pore structure, and presented better flocculation precipitation. The optimal reaction conditions were an initial turbidity of 10 nephelometric turbidity unit(NTU), PATC dosage of 9 mg/L, pH of 8 for the simulated water sample, stirring speed of 50 r/min, and settling time of 50 min, which were determined by Orthogonal experiment. The zeta potential of the reaction process was analyzed. In the treatment of low-turbidity water, PATC mainly functioned by adsorbing, bridging, and sweeping flocculation. Electrical neutralization played an auxiliary role.
Panoramic Image and Three-Axis Laser Scanner Integrated Approach for Indoor 3D Mapping
Authors: Zhao Pengcheng , Hu Qingwu , Wang Shaohua , Ai Mingyao , Mao Qingzhou
Published: August 2018

High-precision indoor three-dimensional maps are a prerequisite for building information models, indoor location-based services, etc., but the indoor mapping solution is still in the stage of technological experiment and application scenario development. In this paper, indoor mapping equipment integrating a three-axis laser scanner and panoramic camera is designed, and the corresponding workflow and critical technologies are described. First, hardware design and software for controlling the operations and calibration of the spatial relationship between sensors are completed. Then, the trajectory of the carrier is evaluated by a simultaneous location and mapping framework, which includes reckoning of the real-time position and attitude of the carrier by a filter fusing the horizontally placed laser scanner data and inertial measurement data, as well as the global optimization by a closed-loop adjustment using a graph optimization algorithm. Finally, the 3D point clouds and panoramic images of the scene are reconstructed from two tilt-mounted laser scanners and the panoramic camera by synchronization of the position and attitude of the carrier. The experiment was carried out in a five-story library using the proposed prototype system; the results demonstrate accuracies of up to 3 cm for 2D maps, and up to 5 cm for 3D maps, and the produced point clouds and panoramic images can be utilized for modeling and further works related to large-scale indoor scenes. Therefore, the proposed system is an efficient and accurate solution for indoor 3D mapping.
A Performance Evaluation of a Geo-Spatial Image Processing Service Based on Open Source PaaS Cloud Computing Using Cloud Foundry on OpenStack
Authors: Lee Kiwon , Kim Kwangseob
Published: August 2018

Recently, web application services based on cloud computing technologies are being offered. In the web-based application field of geo-spatial data management or processing, data processing services are produced or operated using various information communication technologies. Platform-as-a-Service (PaaS) is a type of cloud computing service model that provides a platform that allows service providers to implement, execute, and manage applications without the complexity of establishing and maintaining the lower-level infrastructure components, typically related to application development and launching. There are advantages, in terms of cost-effectiveness and service development expansion, of applying non-proprietary PaaS cloud computing. Nevertheless, there have not been many studies on the use of PaaS technologies to build geo-spatial application services. This study was based on open source PaaS technologies used in a geo-spatial image processing service, and it aimed to evaluate the performance of that service in relation to the Web Processing Service (WPS) 2.0 specification, based on the Open Geospatial Consortium (OGC) after a test application deployment using the configured service supported by a cloud environment. Using these components, the performance of an edge extraction algorithm on the test system in three cases, of 300, 500, and 700 threads, was assessed through a comparison test with another test system, in the same three cases, using Infrastructure-as-a-Service (IaaS) without Load Balancer-as-a-Service (LBaaS). According to the experiment results, in all the test cases of WPS execution considered in this study, the PaaS-based geo-spatial service had a greater performance and lower error rates than the IaaS-based cloud without LBaaS.
SnowCloudHydro—A New Framework for Forecasting Streamflow in Snowy, Data-Scarce Regions
Authors: Sproles Eric A. , Crumley Ryan L. , Nolin Anne W. , Mar Eugene , Lopez Moreno Juan Ignacio
Published: August 2018

We tested the efficacy and skill of SnowCloud, a prototype web-based, cloud-computing framework for snow mapping and hydrologic modeling. SnowCloud is the overarching framework that functions within the Google Earth Engine cloud-computing environment. SnowCloudMetrics is a sub-component of SnowCloud that provides users with spatially and temporally composited snow cover information in an easy-to-use format. SnowCloudHydro is a simple spreadsheet-based model that uses Snow Cover Frequency (SCF) output from SnowCloudMetrics as a key model input. In this application, SnowCloudMetrics rapidly converts NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover product (MOD10A1) into a monthly snow cover frequency for a user-specified watershed area. SnowCloudHydro uses SCF and prior monthly streamflow to forecast streamflow for the subsequent month. We tested the skill of SnowCloudHydro in three snow-dominated headwaters that represent a range of precipitation/snowmelt runoff categories: the Río Elqui in Northern Chile; the John Day River, in the Northwestern United States; and the Río Aragón in Northern Spain. The skill of the SnowCloudHydro model directly corresponded to snowpack contributions to streamflow. Watersheds with proportionately more snowmelt than rain provided better results (R2 values: 0.88, 0.52, and 0.22, respectively). To test the user experience of SnowCloud, we provided the tools and tutorials in English and Spanish to water resource managers in Chile, Spain, and the United States. Participants assessed their user experience, which was generally very positive. While these initial results focus on SnowCloud, they outline methods for developing cloud-based tools that can function effectively across cultures and languages. Our approach also addresses the primary challenges of science-based computing; human resource limitations, infrastructure costs, and expensive proprietary software. These challenges are particularly problematic in countries where scientific and computational resources are underdeveloped.
Buckling-Based Non-Linear Mechanical Sensor
Authors: An Sangmin , Kim Bongsu , Kwon Soyoung , Moon Geol , Lee Manhee , Jhe Wonho
Published: August 2018

Mechanical sensors provide core keys for high-end research in quantitative understanding of fundamental phenomena and practical applications such as the force or pressure sensor, accelerometer and gyroscope. In particular, in situ sensitive and reliable detection is essential for measurements of the mechanical vibration and displacement forces in inertial sensors or seismometers. However, enhancing sensitivity, reducing response time and equipping sensors with a measurement capability of bidirectional mechanical perturbations remains challenging. Here, we demonstrate the buckling cantilever-based non-linear dynamic mechanical sensor which addresses intrinsic limitations associated with high sensitivity, reliability and durability. The cantilever is attached on to a high-Q tuning fork and initially buckled by being pressed against a solid surface while a flexural stress is applied. Then, buckling instability occurs near the bifurcation region due to lateral movement, which allows high-sensitive detection of the lateral and perpendicular surface acoustic waves with bandwidth-limited temporal response of less than 1 ms.
Reliability of 3D Lower Extremity Movement Analysis by Means of Inertial Sensor Technology during Transitional Tasks
Authors: Van der Straaten Rob , Timmermans Annick , Bruijnes Amber K. B. D. , Vanwanseele Benedicte , Jonkers Ilse , De Baets Liesbet
Published: August 2018

This study assesses the reliability and agreement of trunk and lower limb joints’ 3D kinematics, measured by inertial measurement units, during walking and more demanding movement tasks. For data analysis, tasks were divided in open and closed chain phases. Twenty healthy participants were included. On day one, measurements were conducted by “Operator 1” and “Operator 2” to determine between-operator reliability/agreement. On day two, the measurements were conducted by Operator 1, in order to determine within-session reliability/agreement. Furthermore, between-session reliability/agreement was assessed based on data from Operator 1, captured on day one and two. Within-session reliability/agreement was high, and better than between-session and between-operator results for all tasks. The results for walking were generally better than for other movement tasks, for all joint kinematics, and for both open and closed chain phases. Only for the ab/adduction and flexion/extension angles during forward and sideward lunge, reliability and agreement results were comparable to walking, for both the open and closed chain phases. The fact that lunges show similar reliability results than walking for open and closed chain phases, but require more motor control to perform, indicates that the performance of lunges might be interesting to use in further research aiming to identify kinematic differences between populations.
Salivary Detection of Dengue Virus NS1 Protein with a Label-Free Immunosensor for Early Dengue Diagnosis
Authors: Wasik Daniel , Mulchandani Ashok , Yates Marylynn V.
Published: August 2018

Dengue virus (DENV) is a highly pathogenic, arthropod-borne virus transmitted between people by Aedes mosquitoes. Despite efforts to prevent global spread, the potential for DENV epidemics is increasing world-wide. Annually, 3.6 billion people are at risk of infection. With no licensed vaccine, early diagnosis of dengue infection is critical for clinical management and patient survival. Detection of DENV non-structural protein 1 (NS1) is a clinically accepted biomarker for the early detection of DENV infection. Unfortunately, virtually all of the laboratory and commercial DENV NS1 diagnostic methods require a blood draw for sample analysis, limiting point-of-care diagnostics and decreases patient willingness. Alternatively, NS1 in human saliva has been identified for the potential early diagnosis of DENV infection. The collection of saliva is simple, non-invasive, painless, and inexpensive, even by minimally trained personnel. In this study, we present a label-free chemiresistive immunosensor for the detection of the DENV NS1 protein utilizing a network of single-walled carbon nanotubes functionalized with anti-dengue NS1 monoclonal antibodies. NS1 was successfully detected in adulterated artificial human saliva over the range of clinically relevant concentrations with high sensitivity and selectivity. It has potential application in clinical diagnosis and the ease of collection allows for self-testing, even within the home.
A Combined Approach to Predicting Rest in Dogs Using Accelerometers
Authors: Ladha Cassim , Hoffman Christy L.
Published: August 2018

The ability to objectively measure episodes of rest has clear application for assessing health and well-being. Accelerometers afford a sensitive platform for doing so and have demonstrated their use in many human-based trials and interventions. Current state of the art methods for predicting sleep from accelerometer signals are either based on posture or low movement. While both have proven to be sensitive in humans, the methods do not directly transfer well to dogs, possibly because dogs are commonly alert but physically inactive when recumbent. In this paper, we combine a previously validated low-movement algorithm developed for humans and a posture-based algorithm developed for dogs. The hybrid approach was tested on 12 healthy dogs of varying breeds and sizes in their homes. The approach predicted state of rest with a mean accuracy of 0.86 (SD = 0.08). Furthermore, when a dog was in a resting state, the method was able to distinguish between head up and head down posture with a mean accuracy of 0.90 (SD = 0.08). This approach can be applied in a variety of contexts to assess how factors, such as changes in housing conditions or medication, may influence a dog’s resting patterns.
Contact-Lens Biosensors
Authors: Tseng Ryan Chang , Chen Ching-Chuen , Hsu Sheng-Min , Chuang Han-Sheng
Published: August 2018

Rapid diagnosis and screening of diseases have become increasingly important in predictive and preventive medicine as they improve patient treatment strategies and reduce cost as well as burden on our healthcare system. In this regard, wearable devices are emerging as effective and reliable point-of-care diagnostics that can allow users to monitor their health at home. These wrist-worn, head-mounted, smart-textile, or smart-patches devices can offer valuable information on the conditions of patients as a non-invasive form of monitoring. However, they are significantly limited in monitoring physiological signals and biomechanics, and, mostly, rely on the physical attributes. Recently, developed wearable devices utilize body fluids, such as sweat, saliva, or skin interstitial fluid, and electrochemical interactions to allow continuous physiological condition and disease monitoring for users. Among them, tear fluid has been widely utilized in the investigation of ocular diseases, diabetes, and even cancers, because of its easy accessibility, lower complexity, and minimal invasiveness. By determining the concentration change of analytes within the tear fluid, it would be possible to identify disease progression and allow patient-oriented therapies. Considering the emerging trend of tear-based biosensing technology, this review article aims to focus on an overview of the tear fluid as a detection medium for certain diseases, such as ocular disorders, diabetes, and cancer. In addition, the rise and application of minimally invasive detection and monitoring via integrated contact lens biosensors will also be addressed, in regards to their practicality and current developmental progress.
Green Communication for Tracking Heart Rate with Smartbands
Authors: González-Landero Franks , García-Magariño Iván , Lacuesta Raquel , Lloret Jaime
Published: August 2018

The trend of using wearables for healthcare is steeply increasing nowadays, and, consequently, in the market, there are several gadgets that measure several body features. In addition, the mixed use between smartphones and wearables has motivated research like the current one. The main goal of this work is to reduce the amount of times that a certain smartband (SB) measures the heart rate (HR) in order to save energy in communications without significantly reducing the utility of the application. This work has used an SB Sony 2 for measuring heart rate, Fit API for storing data and Android for managing data. The current approach has been assessed with data from HR sensors collected for more than three months. Once all HR measures were collected, then the current approach detected hourly ranges whose heart rate were higher than normal. The hourly ranges allowed for estimating the time periods of weeks that the user could be at potential risk for measuring frequently in these (60 times per hour) ranges. Out of these ranges, the measurement frequency was lower (six times per hour). If SB measures an unusual heart rate, the app warns the user so they are aware of the risk and can act accordingly. We analyzed two cases and we conclude that energy consumption was reduced in 83.57% in communications when using training of several weeks. In addition, a prediction per day was made using data of 20 users. On average, tests obtained 63.04% of accuracy in this experimentation using the training over the data of one day for each user.
Measurement of Unmanned Aerial Vehicle Attitude Angles Based on a Single Captured Image
Authors: Zhang Jin , Ren Lijun , Deng Huaxia , Ma Mengchao , Zhong Xiang , Wen Pengcheng
Published: August 2018

The limited load capacity and power resources of small-scale fixed-wing drones mean that it is difficult to employ internal high-precision inertial navigation devices to assist with the landing procedure. As an alternative, this paper proposes an attitude measurement system based on a monocular camera. The attitude angles are obtained from a single captured image containing five coded landmark points using the radial constraint method and three-dimensional coordinate transformations. The landing procedure is simulated for pitch angles from −15 ∘ to −40 ∘ , roll angles from −15 ∘ to +15 ∘ and yaw angles from −15 ∘ to +15 ∘ . For roll and pitch angles of approximately 0 ∘ and −25 ∘ , respectively, the accuracy of the method reaches 0.01 ∘ and 0.04 ∘ . This UAV attitude measurement system obtains an attitude angle by a single captured image, which has great potential for assisting with the landing of small-scale fixed-wing UAVs.
Motion Blurred Star Image Restoration Based on MEMS Gyroscope Aid and Blur Kernel Correction
Authors: Wang Shiqiang , Zhang Shijie , Ning Mingfeng , Zhou Botian
Published: August 2018

Under dynamic conditions, motion blur is introduced to star images obtained by a star sensor. Motion blur affects the accuracy of the star centroid extraction and the identification of stars, further reducing the performance of the star sensor. In this paper, a star image restoration algorithm is investigated to reduce the effect of motion blur on the star image. The algorithm includes a blur kernel calculation aided by a MEMS gyroscope, blur kernel correction based on the structure of the star strip, and a star image reconstruction method based on scaled gradient projection (SGP). Firstly, the motion trajectory of the star spot is deduced, aided by a MEMS gyroscope. Moreover, the initial blur kernel is calculated by using the motion trajectory. Then, the structure information star strip is extracted by Delaunay triangulation. Based on the structure information, a blur kernel correction method is presented by utilizing the preconditioned conjugate gradient interior point algorithm to reduce the influence of bias and installation deviation of the gyroscope on the blur kernel. Furthermore, a speed-up image reconstruction method based on SGP is presented for time-saving. Simulated experiment results demonstrate that both the blur kernel determination and star image reconstruction methods are effective. A real star image experiment shows that the accuracy of the star centroid extraction and the number of identified stars increase after restoration by the proposed algorithm.
Disney ‘World’: The Westernization of World Music in EPCOT’s “IllumiNations: Reflections of Earth”
Authors: Hodge Matthew
Published: August 2018

Although Disney’s EPCOT theme park markets itself as a place to experience other cultures and reflect on Earth’s history, the dominance of a Western perspective omits true authenticity, specifically in the music of its nighttime show IllumiNations: Reflections of Earth. This 13-minute long presentation offers a visual retelling of humanity’s existence accompanied by an original musical score that guides the narrative. The consecutive music section titles provide insight into critical points within Disney’s story arc: Prologue: Acceleration, Chaos, Space, Life, Adventure, Home, Celebration, and Meaning. While sounds of music from other cultures do present themselves—albeit in stereotypical and clichéd fashions— they are arbitrarily highlighted within a framework of Western musical components. This framing allows Disney composers to control the perception of ‘others’ through music. Furthermore, the final Meaning section is entirely built of Euro-American musical conventions, insinuating that cultures arrive at their most enlightened, evolved selves when they become Westernized. Despite its impressive technological advances and complex musical composition, IllumiNations: Reflections of Earth is guilty of implementing Western musical frameworks that Disney utilizes in the majority of its films and theme parks.
Application of the Vector Measure Construction Method and Technique for Order Preference by Similarity Ideal Solution for the Analysis of the Dynamics of Changes in the Poverty Levels in the European Union Countries
Authors: Piwowarski Mateusz , Miłaszewicz Danuta , Łatuszyńska Małgorzata , Borawski Mariusz , Nermend Kesra
Published: August 2018

In the context of the development of countries, the issue of sustainability is one of the most important aspects that are currently dealt with by scientists and organizations worldwide. There are developed concepts, sustainable development objectives, as well as indicators and tools for measuring sustainability. Following the scientific approach, which aims at operationalization of the concept of sustainable development, the authors propose the application of their own Vector Measure Construction Method for evaluation of sustainable development progress. This method enables creation of aggregated measures with the use of discretionary configuration of indicators and it can be applied for establishing rankings, classifications, and for analyzing dynamics of changes. The research was conducted for European Union countries based on data related to execution of one of 17 Sustainable Development Goals (No Poverty). The results may constitute the recommendation on the selection of methodological approach for activities related to evaluation of sustainable development.
The Impact of Administrative Reform on Labour Market Transformations in Large Polish Cities
Authors: Przybyła Katarzyna , Kachniarz Marian , Hełdak Maria
Published: August 2018

The purpose of the article was to discuss the impact of administrative reforms on the dynamics and the direction of changes occurring in the labour market structure of cities. In the existing research the view prevails that the loss of the voivodship capital function contributes strongly to the socio-economic degradation of the city. In Poland, this discussion has been caused by an administrative reform, as a result of which 49 existing voivodships and the related 49 voivodship capitals were replaced by 16 voivodships and 18 regional capitals. The carried out research focused on both these Polish urban centres which lost their voivodship status and the ones which retained it and become the centres of new, large regions. The Bray-Curtis measure was used to analyse the studied transformations. The data for 2005 and 2016 were used in the research. The conducted study allowed the identification of groups of the cities characterised by a similar range of changes in labour market structure. The research focused on answering the question whether retaining or losing the status of a voivodship city is related to the scale of these changes. The research results presented in the article seem to confirm that the role of administrative changes in the development of cities is not as extensive as it has commonly been attributed. The actual reasons for the economic growth of large centres, or the shrinking of some former voivodship cities, cannot be reduced to the effects of the reform itself. They result, to a much greater extent, from the processes of deindustrialisation, predominantly related to the regression of the declining industry sectors.
Measuring the Readiness of SMEs for Eco-Innovation and Industrial Symbiosis: Development of a Screening Tool
Authors: Pigosso Daniela C. A. , Schmiegelow Andreas , Andersen Maj Munch
Published: August 2018

Despite the high business, innovation and sustainability potential linked with eco-innovation and industrial symbiosis, limited implementation can be observed in small and medium enterprises (SMEs). In order to enhance the implementation of these concepts in SMEs, the main goal of this paper is to propose a screening tool to identify and evaluate SMEs’ potential for eco-innovation, with a special focus on industrial symbiosis and green business models aspects. In order to accomplish this goal, an action research was developed in two cycles: (1) development and testing of the screening prototype; and (2) improvement and scale-up of the enhanced screening tool, in close collaboration with the research partners. In addition to enabling a better understanding about their own internal processes and activities, the evaluation of the potential of 108 SMEs for eco-innovation provided them with detailed insights about how to reach the potential benefits with industrial symbiosis and green business models. Differently from the identified existing tools, the screening tool proposed in this research aims at supporting companies to understand what their potential for eco-innovation is, combining wider eco-innovation and industrial symbiosis opportunities and green business models, supplemented with a readiness evaluation to explore the existing potential.
Regional Innovation Systems as Complex Adaptive Systems: The Case of Lagging European Regions
Authors: Ponsiglione Cristina , Quinto Ivana , Zollo Giuseppe
Published: August 2018

This article proposes an agent-based model to support the development of self-sustaining regional innovation systems (RIS). The model is the base of a computational laboratory, CARIS (Complex Adaptive Regional Innovation System), which aims at evaluating the self-sustainability of RIS and at investigating what are the resources, competencies and mechanisms able to trigger powerful innovation and economic growth processes. Such a topic is particularly interesting for the so-called lagging regions, which, notwithstanding noticeable policy interventions, have been unable to significantly improve their innovation performances. Results of this study show that the exploration capacity, the propensity to cooperation, and the endowed competencies of actors belonging to a region could be considered as key aspects in affecting the regional innovation performance. This means that policy-makers should (i) incentivize investments in research and development activities both at the public and private levels; (ii) support public-private partnerships; (iii) enhance national and regional university systems; and (iv) increase the number of researchers employed both in the public and private sectors. In the next future, the CARIS laboratory could be adopted as policy support instrument to evaluate how much effective are current innovation policies and what are the most effective ones to reassess the current patterns.
A Model for the Optimal Recovery of Multiple Substances from Waste Water with a Focus on Phosphate
Authors: Bongaerts Jan C.
Published: August 2018

In recent times, the issue of a “Phosphate Peak” has entered the academic debate and it is widely present in social media. Arguments in favour and against are similar to those mentioned in the much earlier debate on the “Oil Peak”. However, whereas the “Oil Peak” is supply driven, the “Phosphate Peak”, if at all, is demand driven. In contrast with oil, most of which is chemically transformed in CO2, vapor and other constituting elements, phosphate is not “consumed” during its primary use as a fertilizer. Hence, whilst phosphate rock, from which phosphate is mined, is a depletable resource, phosphate itself is potentially recyclable and re-usable. Research on the technologies for such a recovery is manifold and, specifically, efforts are spent on waste water as a source of phosphate. This, if successful, could lead to a changing perception of waste water treatment plants as a set of backstop technologies to eliminate an environmental problem into a “secondary liquid mine” from which phosphate, but not only phosphate, could be extracted for re-use. Hence, for that purpose, an economic model of efficient extraction of phosphate and other elements from waste water in a waste water treatment plant could give guidance to operators. This paper presents such a model describing the optimal simultaneous extraction of several elements, including phosphate, from a “secondary liquid mine”. The elements are assumed to be present in given proportions (ratios) in this “mine” and the model shows that these ratios have an impact on the optimal extraction path and on resulting “implicit” shadow pricing rules to be adopted by the waste water treatment plant operator.
Evaluating the Driving Risk of Near-Crash Events Using a Mixed-Ordered Logit Model
Authors: Naji Hasan. , Xue Qingji , Lyu Nengchao , Wu Chaozhong , Zheng Ke
Published: August 2018

With the considerable increase in ownership of motor vehicles, traffic crashes have become a challenge. This paper presents a study of naturalistic driving conducted to collect driving data. The experiments were performed on different road types in the city of Wuhan in China. The collected driving data were used to develop a near-crash database, which covers driving behavior, near-crash factors, driving environment, time, demographics, and experience. A new definition of near-crash events is also proposed. The new definition considers potential risks in driving behavior, such as braking pressure, time headway, and deceleration. A clustering analysis was carried out through a K-means algorithm to classify near-crash events based on their risk level. In addition, a mixed-ordered logit model was used to examine the contributing factors associated with the driving risk of near-crash events. The results indicate that ten factors significantly affect the driving risk of near-crash events: deceleration average, vehicle kinetic energy, near-crash causes, congestion on roads, time of day, driving miles, road types, weekend, age, and experience. The findings may be used by transportation planners to understand the factors that influence driving risk and may provide valuable insights and helpful suggestions for improving transportation rules and reducing traffic collisions thus making roads safer.
Assessing the Capacity to Govern Flood Risk in Cities and the Role of Contextual Factors
Authors: Koop Steven , Monteiro Gomes Fabian , Schoot Laura , Dieperink Carel , Driessen Peter , Van Leeuwen Kees
Published: August 2018

Sea level rise and increased storm events urge cities to develop governance capacity. However, a cohesive conceptual and empirical-based understanding of what governance capacity implies, how to measure it, and what cities can learn, is largely lacking. Understanding the influence of context is critical to address this issue. Accordingly, we aim to identify crosscutting contextual factors and how they prioritise different elements of governance capacity to address urban flood risk. In doing so, a framework of nine conditions and 27 indicators is applied in two Dutch cities and two cities in the United Kingdom. Three crosscutting contextual factors are identified that may explain differences in capacity-development priorities: (1) flood probability and impact; (2) national imposed institutional setting; and, (3) level of authority to secure long-term financial support. Capacity-priorities include, the recent political devolution in the UK, which emphasizes the role of citizen awareness, stakeholder engagement, entrepreneurial agents, and the overall necessity for local capacity-development. The Dutch focus on flood safety through centralised public coordination reduces flood probability but inhibits incentives to reduce flood impacts and lowers public awareness. In conclusion, the three identified contextual factors enable a better understanding of capacity-building priorities and may facilitate learning between cities.
Examination of the Status of Financial Inclusion and Its Determinants in Tanzania
Authors: Lotto Josephat
Published: August 2018

The primary motive of this paper is to examine the determinants of financial inclusion in Tanzania. The paper borrows data from a household survey conducted by TWAWEZA. Employing the probit regression, the findings of this paper reveal that gender, education, age and income are the pertinent factors which affect the financial inclusion in Tanzania. The paper further shows the following: First, if you are a man, financially stable, have a good education and are relatively older, you then stand better chances of being financially included. The results show that, as the level of education increases, the individual is more likely to be financially included. The possible reason for this observation may be clearly linked with the financial ability of educated individuals to afford holding bank accounts and presenting personal guarantees when required by the banks during loan application because the level of education goes parallel with the income level. In addition, the results confirm a gender gap in formal financial inclusion, and this may be due to the factors such as inability of women to show collateral, their poor financial education awareness and lower business experience. Second, the paper also shows that the factors which affect traditional banking services are the same as those affecting mobile banking services (gender, age, income and education), and that there is a negative trend and a clear departure of customers’ usage from banking retail services to mobile financial services. Although this gap has been narrowed recently, the best option with the banking sector is to create more new delivery channels while using mobile financial services as an infrastructure to deepen financial access reaching more un-banked population. The paper, therefore, recommends banks to create more delivery channels while using mobile telecommunication network as an infrastructure to deepen financial access reaching more unbanked people rather than competing with mobile network operators. The findings of this paper may also be used as a wake-up call for policy makers to put more emphasis on women and young people who are often left behind during Government’s effort toward reaching the entire population as far as financial inclusion is concerned.
The Prism of Elasticity in Rebound Effect Modelling: An Insight from the Freight Transport Sector
Authors: Ruzzenenti Franco
Published: August 2018

If the rebound effect is to be considered a major obstacle to sustainable freight transport, then action and timely policy must be made in advance. This, however, requires a theoretical understanding of the nature of the rebound effect and an empirical grasp of its underlying mechanism. Elasticity is the centrepiece of current models on the rebound effect (or Jevons paradox). Although elasticity is a metric of indisputable usefulness for empirical purposes, it may be misleading when applied to the complex rebound effect. Drawing on the parallel case of the ‘distance puzzle’ in international economics, it will be shown how elasticity can be misinterpreted or how it can misdirect an investigation of the phenomenon by following a predetermined mindset. This particular bias is shown to widen in the long term and evolving systems in which the elasticity metric continues to output a constant number, eliciting a persistent effect. Drawing on previous research, an alternative approach to studying the rebound effect based on complex network theory and statistical mechanics of networks will be described. It will be shown how the interplay between spatial and non-spatial effects in freight transport networks can inform us about the evolution of the effect of distances on trade relationships, upon which a new metric for the rebound effect can be built.
Quantifying the Role of Large Floods in Riverine Nutrient Loadings Using Linear Regression and Analysis of Covariance
Authors: Verma Siddhartha , Bartosova Alena , Markus Momcilo , Cooke Richard , Um Myoung-Jin , Park Daeryong
Published: August 2018

This study analyzes the role of large river flow events in annual loads, for three constituents and for up to 32 years of daily data at multiple watersheds with different land-uses. Prior studies were mainly based on simple descriptive statistics, such as the percentage of nutrient loadings transported during several of the largest river flows, while this study uses log-regression and analysis of covariance (ANCOVA) to describe and quantify the relationships between large flow events and nutrient loadings. Regression relationships were developed to predict total annual loads based on loads exported by the largest events in a year for nitrate plus nitrite nitrogen (NO3-N + NO2-N, indicated as total oxidized nitrogen; TON), total phosphorus (TP), and suspended solids (SS) for eight watersheds in the Lake Erie and Ohio River basins. The median prediction errors for annual TON, TP, and SS loads from the top five load events for spatially aggregated watersheds were 13.2%, 18.6%, and 13.4%, respectively, which improve further on refining the spatial scales. ANCOVA suggests that the relationships between annual loads and large load events are regionally consistent. The findings outline the dominant role of large hydroclimatic events, and can help to improve the design of pollutant monitoring and agricultural conservation programs.
Risk Mapping of Visceral Leishmaniasis: A Spatial Regression Model for Attica Region, Greece
Authors: Iliopoulou Polixeni , Tsatsaris Andreas , Katsios Ioannis , Panagiotopoulou Amalia , Romaliades Stelios , Papadopoulos Byron , Tselentis Yannis
Published: August 2018

Visceral Leishmaniasis (VL) is endemic to the Attica region of Greece. The geographical distribution of VL cases was analyzed employing methods of spatial analysis in a GIS environment. A geographic database was constructed including data for the disease cases and environmental factors, such as land cover types, stray dog population, and socioeconomic factors. Classic and spatial regression models are presented that suggest the factors contributing most to the incidence of leishmaniasis are green urban areas and the population of stray dogs in the municipalities of Attica region. The results of the spatial regression model were more accurate, thus were used to produce a disease risk map. This map indicates the high-risk municipalities in which surveillance for the control of leishmaniasis is necessary.