bluuebunny/crossref_metadata_2025 huggingface dataset:
Stability and Compatibility Studies of Levothyroxine Sodium in Solid Binary Systems—Instrumental Screening
Authors: Ledeți Ionuț , Romanescu Mirabela , Cîrcioban Denisa , Ledeți Adriana , Vlase Gabriela , Vlase Titus , Suciu Oana , Murariu Marius , Olariu Sorin , Matusz Petru , Buda Valentina , Piciu Doina
Published: January 2020

The influence of excipients on the stability of sodium levothyroxine pentahydrate (LTSS) under ambient conditions and thermal stress was evaluated. Since LTSS is a synthetic hormone with a narrow therapeutic index, the interactions of LTSS with excipients can lead to a drastic diminution of therapeutic activity. Ten commonly used pharmaceutical excipients with different roles in solid formulations were chosen as components for binary mixtures containing LTSS, namely, starch, anhydrous lactose, D-mannitol, D-sorbitol, gelatin, calcium lactate pentahydrate, magnesium stearate, methyl 2-hydroxyethyl cellulose (Tylose), colloidal SiO2 (Aerosil) and talc. As investigational tools, universal attenuated total reflectance- Fourier transform infrared spectroscopy UATR-FTIR spectroscopy and thermal analysis were chosen and used as follows: UATR-FTIR spectra were drawn up for samples kept under ambient conditions, while thermoanalytical tools (TG/DTG/HF data) were chosen to evaluate the inducing of interactions during thermal stress. The corroboration of instrumental results led to the conclusion that LTSS is incompatible with lactose, mannitol and sorbitol, and these excipients should not be considered in the development of new generic solid formulations.
Acknowledgement to Reviewers of Polymers in 2019
Authors:   Polymers Editorial Office
Published: January 2020

The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not [...]
Flexible Electrode Based on MWCNT Embedded in a Cross-Linked Acrylamide/Alginate Blend: Conductivity vs. Stretching
Authors: Thibodeau Jake , Ignaszak Anna
Published: January 2020

A polyacrylamide-alginate hydrogel electrolyte, blended with Multi-Walled Carbon Nanotubes (MWCNT) as an electronically conductive fraction, allows for the creation of a flexible, durable, and resilient electrode. The MWCNT content is correlated with mechanical characteristics such as stretch modulus, tensile resistance, and electrical conductivity. The mechanical analysis demonstrates tensile strength that is comparable to similar hydrogels reported in the literature, with increasing strength for MWCNT-embedded hydrogels. The impedance spectroscopy reveals that the total resistance of electrodes decreases with increasing MWCNT content upon elongation and that bending and twisting do not obstruct their conductivity. The MWCNT-inserted hydrogels show mixed ionic and electronic conductivities, both within a range of 1–4 × 10−2 S cm−1 in a steady state. In addition, the thermal stability of these materials increases with incrementing MWCNT content. This observation agrees with long-term charge-discharge cycling that shows enhanced electrochemical durability of the MWCNT-hydrogel hybrid when compared to pure hydrogel electrolyte. The hydrogel-carbon films demonstrate an increased interfacial double-layer current at a high MWCNT content (giving an area-specific capacitance of ~30 mF cm−2 at 2.79 wt.% of MWCNT), which makes them promising candidates as printable and flexible electrodes for lightweight energy storage applications. The maximum content of MWCNT within the polymer electrolyte was estimated at 2.79 wt.%, giving a very elastic polymer electrode with good electrical characteristics.
Thermal Cracking Furnace Optimal Modeling Based on Enriched Kumar Model by Free-Radical Reactions
Authors: Mu Peng , Gu Xiangbai
Published: January 2020

The Kumar model as a molecular model has achieved successful application. However, only 22 reactions limit its veracity and adaptability for feedstocks. A series of models with different degrees of integration of the free radical model and the molecular model has been proposed to enhance feedstock adaptability and simulation accuracy. An improved search engine algorithm, namely Improved PageRank (IPR), is provided and applied to calculate the importance of substances in Kumar model to screen the free-radical reaction network for efficient model selection. A methodology of optimal structure and model parameters chosen is applied to the target to improve the adaptability of the material and the accuracy of the model. Then, two cases with different feedstocks are demonstrated with industrial data to verify the correctness of the proposed approach and its wide feedstock adaptability. The proposed model demonstrates good performance: (1) The mean relative errors (MRE) of the K-R (Kumar and free-radical) model have reached an order of magnitude less than 0.1% compared with 5% in the Kumar model. Further, (2) the K-R model can be implemented to model some feedstocks which Kumar model can’t simulate successfully. The K-R model can be applied in simulation of extensive feedstocks with high accuracy.
Experimental Study on the Effect of Polymer Injection Timing on Oil Displacement in Porous Media
Authors: Shi Leiting , Zhu Shijie , Guo Zhidong , Zhao Wensen , Xue Xinsheng , Wang Xiao , Ye Zhongbin
Published: January 2020

It has been proven that polymer injection at early times is beneficial to offshore heavy oil recovery. It is of significant importance to optimize the polymer injection timing and decide the residual oil distribution after polymer flooding. Aiming at a specific offshore heavy oil reservoir in Bohai, China, the optimum polymer injection timing is investigated through laboratory experiments. The influence of polymer injection timing on oil displacement and remaining oil distribution is analyzed by combining macroscopic and microscopic flooding experiments. The results reveal that the optimum polymer injection timing should be close to the water breakthrough, i.e., just before the waterflooding front reaches the outlet of the core. In addition, the waterflooding front position is analytically solved by using the Buckley–Leverett method and verified by experimental results, which supply an approach to predict the polymer injection timing. When polymer is injected before the waterflood front reaches the outlet of the core, the mobility control ability of polymer solution can reduce the fraction of bypassed volume of the reservoir by waterflooding. The early injected polymer mainly enters the high permeability zone, which works positively in two ways. Firstly, it improves the oil displacement efficiency of the high permeability zone. Secondly, the polymer establishes a flow resistance in the high permeable zones, thus improving the sweep efficiency in the low and medium permeability zones. However, our residual oil distribution experiments illustrate that there is still a large amount of oil remaining in the low and medium permeability zones. Therefore, it is necessary to explore additional EOR methods to recover the abundant residual oil.
3D Modeling of Discontinuity in the Spatial Distribution of Apartment Prices Using Voronoi Diagrams
Authors: Bełej Mirosław , Figurska Marta
Published: January 2020

An immanent feature of the housing market is a large spatial dispersion of real estate prices along with their simultaneous high stratification. Application of classic methods of data interpolation results in an excessive simplification of the outcome because of a conversion of the dispersed data sets into areas of spatial continuity by reducing the above-average real estate prices. The main aim of the article was to search for spatial discontinuities of real estate prices’ distribution with 3D modeling using Voronoi diagrams as a method of irregular division of this space. Used methods of geospatial analyses with GIS tools enabled to identify clusters of high housing market activity and to avoid an excessive generalization of data resulting from the reduction of the above-average real estate prices. The research was conducted for over 7000 real estate transactions in years 2010–2017 in Olsztyn, the capital city of Warmia and Mazury in Poland, resulting in a 3D visualization of real estate prices for the chosen market, including the discontinuity in their spatial distribution.
Study of Human Thermal Comfort for Cyber–Physical Human Centric System in Smart Homes
Authors: Fang Yuan , Lim Yuto , Ooi Sian En , Zhou Chenmian , Tan Yasuo
Published: January 2020

An environmental thermal comfort model has previously been quantified based on the predicted mean vote (PMV) and the physical sensors parameters, such as temperature, relative humidity, and air speed in the indoor environment. However, first, the relationship between environmental factors and physiology parameters of the model is not well investigated in the smart home domain. Second, the model that is not mainly for an individual human model leads to the failure of the thermal comfort system to fulfill the human’s comfort preference. In this paper, a cyber–physical human centric system (CPHCS) framework is proposed to take advantage of individual human thermal comfort to improve the human’s thermal comfort level while optimizing the energy consumption at the same time. Besides that, the physiology parameter from the heart rate is well-studied, and its correlation with the environmental factors, i.e., PMV, air speed, temperature, and relative humidity are deeply investigated to reveal the human thermal comfort level of the existing energy efficient thermal comfort control (EETCC) system in the smart home environment. Experimental results reveal that there is a tight correlation between the environmental factors and the physiology parameter (i.e., heart rate) in the aspect of system operational and human perception. Furthermore, this paper also concludes that the current EETCC system is unable to provide the precise need for thermal comfort to the human’s preference.
Extended Phase Unwrapping Max-Flow/Min-Cut Algorithm for Multibaseline SAR Interferograms Using a Two-Stage Programming Approach
Authors: Zhou Lifan , Lan Yang , Xia Yu , Gong Shengrong
Published: January 2020

Multi-baseline (MB) phase unwrapping (PU) is a key step of MB synthetic aperture radar (SAR) interferometry (InSAR). Compared with the traditional single-baseline (SB) PU, MB PU is applicable to the area where topography varies violently without obeying the phase continuity assumption. A two-stage programming MB PU approach (TSPA) proposed by H. Yu. builds the link between SB and MB PUs, so many existing classical SB PU methods can be transplanted into the MB domain. In this paper, an extended PU max-flow/min-cut (PUMA) algorithm for MB InSAR using the TSPA, referred to as TSPA-PUMA, is proposed, consisting of a two-stage programming procedure. In stage 1, phase gradients are estimated based on Chinese remainder theorem (CRT). In stage 2, a Markov random field (MRF) model of PUMA is designed for modeling local contextual dependence based on the phase gradients obtained by stage 1. Subsequently, the energy of the MRF model is minimized by graph cuts techniques. The experiment results illustrate that the TSPA-PUMA method can drastically enhance the accuracy of the original PUMA method in the rugged area, and is more efficient than the original TSPA method. In addition, the noise robustness of TSPA-PUMA can be improved through adding more interferograms with different baseline lengths.
Trajectory-Based Air-Writing Recognition Using Deep Neural Network and Depth Sensor
Authors: Alam Md. Shahinur , Kwon Ki-Chul , Alam Md. Ashraful , Abbass Mohammed Y. , Imtiaz Shariar Md , Kim Nam
Published: January 2020

Trajectory-based writing system refers to writing a linguistic character or word in free space by moving a finger, marker, or handheld device. It is widely applicable where traditional pen-up and pen-down writing systems are troublesome. Due to the simple writing style, it has a great advantage over the gesture-based system. However, it is a challenging task because of the non-uniform characters and different writing styles. In this research, we developed an air-writing recognition system using three-dimensional (3D) trajectories collected by a depth camera that tracks the fingertip. For better feature selection, the nearest neighbor and root point translation was used to normalize the trajectory. We employed the long short-term memory (LSTM) and a convolutional neural network (CNN) as a recognizer. The model was tested and verified by the self-collected dataset. To evaluate the robustness of our model, we also employed the 6D motion gesture (6DMG) alphanumeric character dataset and achieved 99.32% accuracy which is the highest to date. Hence, it verifies that the proposed model is invariant for digits and characters. Moreover, we publish a dataset containing 21,000 digits; which solves the lack of dataset in the current research.
Optimization of Ring Laser Gyroscope Bias Compensation Algorithm in Variable Temperature Environment
Authors: Weng Jun , Bian Xiaoyun , Kou Ke , Lian Tianhong
Published: January 2020

In a high accuracy strapdown inertial navigation system (SINS), the ring laser gyroscope’s (RLG) bias changes and the performance decreases due to factors in the RLG’s self-heating and changes in ambient temperature. Therefore, it is important to study the bias temperature drift characteristics of RLGs in high, low, and variable temperature environments. In this paper, a composite temperature calibration scheme is proposed. The composite temperature model introduces the derivative term and the temperature derivative cross-multiplier on the basis of the static model and sets the overlap regions for the piecewise least squares fitting. The results show that the composite temperature model can compensate the bias trend term well at ambient temperature, improve the fitting accuracy, and smooth the output curve. The compensation method has a small amount of calculations and flexible parameter design. The precision of the laser gyros in one SINS is improved by about 64.9%, 15.7%, and 3.6%, respectively, which has certain engineering application value.
Complex MIMO RBF Neural Networks for Transmitter Beamforming over Nonlinear Channels
Authors: Soares Mayer Kayol , Aguiar Soares Jonathan , Soares Arantes Dalton
Published: January 2020

The use of beamforming for efficient transmission has already been successfully implemented in practical systems and is absolutely necessary to even further increase spectral and energy efficiencies in some configurations of the next-generation wireless systems and for low earth orbit satellites. A remarkable capacity increase is then achieved and spectral congestion is minimized. In this context, this article proposes a novel complex multiple-input multiple-output radial basis function neural network (CMM-RBF) for transmitter beamforming, based on the phase transmittance radial basis function neural network (PTRBFNN). The proposed CMM-RBF is compared with the least mean square (LMS) algorithm for beamforming with six dipoles arranged in a uniform and circular array and with 16 dipoles in a 2D-grid array. Simulation results show that the proposed solution presents lower steady-state mean squared error, faster convergence rate and enhanced half-power beamwidth (HPBW) when compared with the LMS algorithm in a nonlinear scenario.
Identification of Tiny Surface Cracks in a Rugged Weld by Signal Gradient Algorithm Using the ACFM Technique
Authors: Yuan Xin’an , Li Wei , Yin Xiaokang , Chen Guoming , Zhao Jianming , Jiang Weiyu , Ge Jiuhao
Published: January 2020

It is still a big challenge to identify tiny surface cracks in a rugged weld due to the lift-off variations using the nondestructive testing (NDT) method. In this paper, the signal gradient algorithm is presented to identify the tiny surface crack in the rugged weld using the alternating current field measurement (ACFM) technique. The ACFM simulation model and testing system was set up to obtain the insensitive signal to the lift-off variations. The signal gradient algorithm was presented to process the insensitive signal for the identification of the tiny surface crack in the rugged weld. The results show that the Bz signal is the insensitive signal to lift-off variations caused by the rugged weld. The signal to noise ratio (SNR) of the crack identification signal was greatly improved by the signal gradient algorithm, and a tiny surface crack can be identified effectively in the weld and the heat affected zone (HAZ).
Investigation on X-ray Photocurrent Response of CdZnTe Photon Counting Detectors
Authors: Li Yingrui , Zha Gangqiang , Guo Yu , Xi Shouzhi , Xu Lingyan , Jie Wanqi
Published: January 2020

Counting rate is an important factor for CdZnTe photon counting detectors as high-flux devices. Until recently, there has been a lack of knowledge on the relationship between X-ray photocurrent response and the photon counting performance of CdZnTe detectors. In this paper, the performance of linear array 1 × 16-pixel CdZnTe photon counting detectors operated under different applied biases is investigated. The relation between experimental critical flux and applied bias show an approximate quadratic dependence, which agrees well the theoretical prediction. The underlying relationship among X-ray photocurrents, carrier transport properties, and photon counting performance was obtained by analyzing X-ray current–voltage and time current curves. The typical X-ray photocurrent curve can be divided into three regions, which may be explained by the photoconductive gain mechanism and electric field distortion characteristics. To keep CdZnTe photon counting detectors working in a “non-polarized state”, the applied bias should be set on the left side of the “valley region” (high bias direction) in the X-ray I-V curves. This provides an effective measurement for determining the proper working bias of CdZnTe detectors and screening photon counting detector crystals.
Thermal Modeling and Calibration Method in Complex Temperature Field for Single-Axis Rotational Inertial Navigation System
Authors: Wang Zihui , Cheng Xianghong , Du Jingjing
Published: January 2020

Single-axis rotational inertial navigation systems (single-axis RINSs) are widely used in high-accuracy navigation because of their ability to restrain the horizontal axis errors of the inertial measurement unit (IMU). The IMU errors, especially the biases, should be constant during each rotation cycle that is to be modulated and restrained. However, the temperature field, consisting of the environment temperature and the power heating of single-axis RINS, affects the IMU performance and changes the biases over time. To improve the precision of single-axis RINS, the change of IMU biases caused by the temperature should be calibrated accurately. The traditional thermal calibration model consists of the temperature and temperature change rate, which does not reflect the complex temperature field of single-axis RINS. This paper proposed a multiple regression method with a temperature gradient in the model, and in order to describe the complex temperature field thoroughly, a BP neural network method is proposed with consideration of the coupled items of the temperature variables. Experiments show that the proposed methods outperform the traditional calibration method. The navigation accuracy of single-axis RINS can be improved by up to 47.41% in lab conditions and 65.11% in the moving vehicle experiment, respectively.
Effects of Brownfield Remediation on Total Gaseous Mercury Concentrations in an Urban Landscape
Authors: Meng Linghui , T. Driscoll Charles , Montesdeoca Mario , Mao Huiting
Published: January 2020

In order to obtain a better perspective of the impacts of brownfields on the land–atmosphere exchange of mercury in urban areas, total gaseous mercury (TGM) was measured at two heights (1.8 m and 42.7 m) prior to 2011–2012 and after 2015–2016 for the remediation of a brownfield and installation of a parking lot adjacent to the Syracuse Center of Excellence in Syracuse, NY, USA. Prior to brownfield remediation, the annual average TGM concentrations were 1.6 ± 0.6 and 1.4 ± 0.4 ng · m − 3 at the ground and upper heights, respectively. After brownfield remediation, the annual average TGM concentrations decreased by 32% and 22% at the ground and the upper height, respectively. Mercury soil flux measurements during summer after remediation showed net TGM deposition of 1.7 ng · m − 2 · day − 1 suggesting that the site transitioned from a mercury source to a net mercury sink. Measurements from the Atmospheric Mercury Network (AMNet) indicate that there was no regional decrease in TGM concentrations during the study period. This study demonstrates that evasion from mercury-contaminated soil significantly increased local TGM concentrations, which was subsequently mitigated after soil restoration. Considering the large number of brownfields, they may be an important source of mercury emissions source to local urban ecosystems and warrant future study at additional locations.
Multi-Angle Liquid Flow Measurement Using Ultrasonic Linear Array Transducer
Authors: Nguyen Thi Huong Ly , Park Suhyun
Published: January 2020

Most ultrasonic flowmeters utilize several wedge sensors for transmission and reception. Thus, the location and alignment of the sensors are critical factors that determine the performance of the ultrasonic flowmeter. In this study, we proposed an ultrasound liquid flowmeter utilizing a 128-element linear array transducer with a transmit delay control for varying the incidence angles of ultrasound wave transmission. The performance of the flowmeter was evaluated at flow rates of 0–50 L/min in a specially designed pipe system. Flow estimation was performed with the transit-time method using cross-correlation with phase zero-crossing for sub-sample estimation. While a single plane wave approach performed invasive electromagnetic measurements with only 74% accuracy as a reference, a multiple angular compensation method with 24 angles was proposed to increase the accuracy of measurements up to 93%. This study demonstrated the capability of the non-invasive single-sided ultrasonic flowmeter with a linear array transducer for liquid flow measurements in the metal pipe system.
Reservoir Dam Surface Deformation Monitoring by Differential GB-InSAR Based on Image Subsets
Authors: Wang Peng , Xing Cheng , Pan Xiandong
Published: January 2020

Ground-based synthetic aperture radar interferometry (GB-InSAR) enables the continuous monitoring of areal deformation and can thus provide near-real-time control of the overall deformation state of dam surfaces. In the continuous small-scale deformation monitoring of a reservoir dam structure by GB-InSAR, the ground-based synthetic aperture radar (GB-SAR) image acquisition may be interrupted by multiple interfering factors, such as severe changes in the meteorological conditions of the monitoring area and radar equipment failures. As a result, the observed phases before and after the interruption cannot be directly connected, and the original spatiotemporal datum for the deformation measurement is lost, making the follow-up monitoring results unreliable. In this study, a multi-threshold strategy was first adopted to select coherent point targets (CPTs) by using successive GB-SAR image sequences. Then, we developed differential GB-InSAR with image subsets based on the CPTs to solve the dam surface deformation before and after aberrant interruptions. Finally, a deformation monitoring experiment was performed on an actual large reservoir dam. The effectiveness and accuracy of the abovementioned method were verified by comparing the results with measurements by a reversed pendulum monitoring system.
Intelligent Object Recognition of Urban Water Bodies Based on Deep Learning for Multi-Source and Multi-Temporal High Spatial Resolution Remote Sensing Imagery
Authors: Song Shiran , Liu Jianhua , Liu Yuan , Feng Guoqiang , Han Hui , Yao Yuan , Du Mingyi
Published: January 2020

High spatial resolution remote sensing image (HSRRSI) data provide rich texture, geometric structure, and spatial distribution information for surface water bodies. The rich detail information provides better representation of the internal components of each object category and better reflects the relationships between adjacent objects. In this context, recognition methods such as geographic object-based image analysis (GEOBIA) have improved significantly. However, these methods focus mainly on bottom-up classifications from visual features to semantic categories, but ignore top-down feedback which can optimize recognition results. In recent years, deep learning has been applied in the field of remote sensing measurements because of its powerful feature extraction ability. A special convolutional neural network (CNN) based region proposal generation and object detection integrated framework has greatly improved the performance of object detection for HSRRSI, which provides a new method for water body recognition based on remote sensing data. This study uses the excellent “self-learning ability” of deep learning to construct a modified structure of the Mask R-CNN method which integrates bottom-up and top-down processes for water recognition. Compared with traditional methods, our method is completely data-driven without prior knowledge, and it can be regarded as a novel technical procedure for water body recognition in practical engineering application. Experimental results indicate that the method produces accurate recognition results for multi-source and multi-temporal water bodies, and can effectively avoid confusion with shadows and other ground features.
Validity and Reliability of an Inertial Device for Measuring Dynamic Weight-Bearing Ankle Dorsiflexion
Authors: Oliva-Lozano José M. , Martín-Fuentes Isabel , Muyor José M.
Published: January 2020

A decrease in ankle dorsiflexion causes changes in biomechanics, and different instruments have been used for ankle dorsiflexion testing under static conditions. Consequently, the industry of inertial sensors has developed easy-to-use devices, which measure dynamic ankle dorsiflexion and provide additional parameters such as velocity, acceleration, or movement deviation. Therefore, the aims of this study were to analyze the concurrent validity and test-retest reliability of an inertial device for measuring dynamic weight-bearing ankle dorsiflexion. Sixteen participants were tested using an inertial device (WIMU) and a digital inclinometer. Ankle dorsiflexion from left and right ankle repetitions was used for validity analysis, whereas test-retest reliability was analyzed by comparing measurements from the first and second days. The standard error of the measurement (SEM) between the instruments was very low for both ankle measurements (SEM < 0.6°). No significant differences between instruments were found for the left ankle measurement (p > 0.05) even though a significant systematic bias (~1.77°) was found for the right ankle (d = 0.79). R2 was very close to 1 in the left and right ankles (R2 = 0.85–0.89) as well as the intraclass correlation coefficient (ICC > 0.95). Test-retest reliability analysis showed that systematic bias was below 1° for both instruments, even though a systematic bias (~1.50°) with small effect size was found in the right ankle (d = 0.49) with WIMU. The ICC was very close to 1 and the coefficient of variation (CV) was lower than 4% in both instruments. Thus, WIMU is a valid and reliable inertial device for measuring dynamic weight-bearing ankle dorsiflexion.
Analysis and Design of Interruptible Gas Contract in China under Energy Market Reform
Authors: Chai Jian , Wang Liqiao
Published: January 2020

Under the background of economic development, energy security and environmental demands, the development of clean and low-carbon energy has promoted natural gas and non-fossil energy to become the main direction of world energy development. China’s natural gas consumer market has wide seasonal peaks and valleys. Because China’s natural gas peak shaving practices have some problems, we concluded that interruptible gas management has become a viable short-term emergency peak shaving method for natural gas systems in the transition period. In this paper, we take Shaanxi Province as an example. From the perspective of option pricing, this paper explains the method of using interruptible gas management to deal with the short-term supply and demand imbalance of natural gas. Therefore, we propose an interruptible gas contract trading mode, discuss the content of the interruptible gas contract and the relevant market organization form, and try to use the Black–Scholes model to calculate the option price of the interruptible gas contract. Finally, based on the price of interruptible gas and the option price of the interruptible gas contract to meet the maximum capacity shortage constraint, a provincial natural gas pipeline network company’s optimal purchase model for the interruptible gas was established, and the model was solved using the dynamic queuing method. The results show that the interruptible gas contract can not only reduce the market risk of the provincial natural gas pipeline network company and maintain the stable operation of the gas pipeline, but also reduce the cost of the interruptible users and make up for gas shortage losses.
Global Sourcing in Fast Fashion Retailers: Sourcing Locations and Sustainability Considerations
Authors: Arrigo Elisa
Published: January 2020

For decades, apparel companies have profited from moving their manufacturing to low-cost countries and several academic studies have focused on understanding whether low-cost locations could support optimal supply chain configurations. However, the exploitation of resources in foreign sourcing countries often resulted in many environmental and social issues and apparel companies became progressively more concerned about the negative exposure that they could face with a limited supply chain transparency. Therefore, this paper aims at investigating global sourcing strategies of fast fashion retailers in order to understand whether the decision criteria influencing sourcing locations have changed over time to also embrace sustainability considerations. Drawing on a literature review on sustainability in fashion supply chains, offshore outsourcing, and fast fashion global sourcing, a new theoretical framework concerning fast fashion retailers’ sourcing locations is proposed together with a content analysis of their reports. The findings show that fast fashion retailers identify sustainability as a key element to consider in selecting sourcing locations since sustainability issues at suppliers’ factories may represent relevant hidden costs. Moreover, actions aimed at checking and improving sustainable practices in global sourcing policies are proven to support the development of a strategic sourcing reputation for their fast fashion brands.
Venice and Overtourism: Simulating Sustainable Development Scenarios through a Tourism Carrying Capacity Model
Authors: Bertocchi Dario , Camatti Nicola , Giove Silvio , van der Borg Jan
Published: January 2020

Overtourism problems, anti-tourist movements and negative externalities of tourism are popular research approaches and are key concepts to better understand the sustainable development of tourism destinations. In many of the overtourism narratives, Venice is considered to be one of the most relevant cases of overtourism and therefore has become a laboratory for studying the different conflicts that emerge when tourism numbers continue to grow and the quality of the tourism flow continues to decline. This article is therefore focusing on Venice and on one of the possible solutions to mitigate the negative impacts of tourism represented by the concept of a tourist carrying capacity (TCC) in an urban destination. The aim of this paper is to discuss alternative methodologies regarding the calculation of the TCC, and to apply a fuzzy instead of a ‘crisp’ linear programming model to determine the scenarios of a sustainable number of tourists in the cultural destination of Venice, looking for the optimal compromise between, on the one hand, the wish of maximizing the monetary gain by the local tourism sectors and, on the other, the desire to control the undesirable effects that tourism exerts on a destination by the local population. To solve the problems related to tourism statistics and data availability, some uncertainty in the parameters has been included using fuzzy numbers. The fuzziness in the model was introduced on the basis of questionnaires distributed among both tourists and residents. By applying the fuzzy linear programming model to the emblematic case of Venice, it was shown that this approach can indeed help destinations to understand the challenges of sustainable tourism development better, to evaluate the impact of alternative policies of overtourism on the sustainability of tourism, and hence, to help design a strategy to manage tourist flows more adequately
Curvature Invariants for Lorentzian Traversable Wormholes
Authors: Mattingly Brandon , Kar Abinash , Julius William , Gorban Matthew , Watson Cooper , Ali MD , Baas Andrew , Elmore Caleb , Shakerin Bahram , Davis Eric , Cleaver Gerald
Published: January 2020

The curvature invariants of three Lorentzian wormholes are calculated and plotted in this paper. The plots may be inspected for discontinuities to analyze the traversability of a wormhole. This approach was formulated by Henry, Overduin, and Wilcomb for black holes (Henry et al., 2016). Curvature invariants are independent of coordinate basis, so the process is free of coordinate mapping distortions and the same regardless of your chosen coordinates (Christoffel, E.B., 1869; Stephani, et al., 2003). The four independent Carminati and McLenaghan (CM) invariants are calculated and the nonzero curvature invariant functions are plotted (Carminati et al., 1991; Santosuosso et al., 1998). Three traversable wormhole line elements analyzed include the (i) spherically symmetric Morris and Thorne, (ii) thin-shell Schwarzschild wormholes, and (iii) the exponential metric (Visser, M., 1995; Boonserm et al., 2018).
Fetal Calf Serum Exerts an Inhibitory Effect on Replication of Duck Hepatitis A Virus Genotype 1 in Duck Embryo Fibroblast Cells
Authors: Wang Minghang , Chai Lili , Liang Suyun , Lv Junfeng , Yang Lixin , Qu Shenghua , Jin Meiling , Li Qingxiangzi , Wang Xiaoyan , Zhang Dabing
Published: January 2020

Among the causative agents of duck viral hepatitis, duck hepatitis A virus genotype 1 (DHAV-1) is the most common virus reported in most outbreaks worldwide. How to propagate DHAV-1 in cell cultures efficiently remains a problem to be explored. Here, we aimed to test the effect of serum type on DHAV-1 replication in duck embryo fibroblast (DEF) cells. Comparative studies involved virus culture and passage, observation of cytopathic effect (CPE), virus quantification, and plaque formation assay. From the results of these investigations, we conclude that use of chicken serum (CS) in maintenance medium allows DHAV-1 to establish productive, cytocidal infection in DEF cells, whereas FCS exerts inhibitory effects on DHAV-1 replication, CPE development, and plaque formation. By using a neutralization test, we found that the direct action of FCS on virions is likely to play a key role in inhibiting DHAV-1 replication in DEF cells. Mechanism analyses revealed that FCS inhibits DHAV-1 replication at virus adsorption and reduces extracellular virus yields. The present work may shed light on a new perspective for antiviral agent development, and have provided a virus–host cell system for further studies on molecular mechanism involved DHAV-1 replication and pathogenesis.
The Unknown Health Burden of Herpes Zoster Hospitalizations: The Effect on Chronic Disease Course in Adult Patients ≥50 Years
Authors: Piazza Maria Francesca , Paganino Chiara , Amicizia Daniela , Trucchi Cecilia , Orsi Andrea , Astengo Matteo , Romairone Paolo , Simonetti Simona , Icardi Giancarlo , Ansaldi Filippo
Published: January 2020

The effect of severe Herpes Zoster (HZ) on chronic diseases is a component of the real burden of this vaccine-preventable disease that is not commonly considered. A retrospective cohort study was conducted to assess the health burden of severe HZ in adults ≥50 years residing in Liguria Region from 2015 to 2017. Subjects hospitalized with and without HZ were matched (1:6 ratio). 437 subjects in the HZ cohort and 2622 subjects in the non-HZ cohort were enrolled. Previous immunodeficiency, autoimmune, and rare diseases are identified as main chronic conditions related to HZ hospitalization. Higher incidences of autoimmune (1.4% vs. 0.22%, p = 0.002) and gastrointestinal (7.04% vs. 3.62%, p = 0.015) diseases after hospitalization were observed in the HZ cohort compared to the non-HZ cohort. Significantly higher incidences were found after hospitalization versus the previous period for cardiovascular diseases (11.17% vs. 2.09%, p < 0.001), cerebral vasculopathy (6.13% vs. 0.60%, p < 0.001), non-arrhythmic myocardiopathy (4.31% vs. 0.59%, p = 0.002), and neuropathy (2.62% vs. 0.56%, p = 0.033). The HZ cohort showed a relative risk 10-fold higher for cerebral vasculopathy, 5-fold higher for cardiovascular diseases, and 7-fold higher for non-arrhythmic myocardiopathy. HZ causes a substantial impact on the chronic conditions. These data could suggest an implementation of HZ vaccination programs in the elderly and in high-risk groups.
Alternative Vaccination Routes against Paratuberculosis Modulate Local Immune Response and Interference with Tuberculosis Diagnosis in Laboratory Animal Models
Authors: Arrazuria Rakel , Ladero Iraia , Molina Elena , Fuertes Miguel , Juste Ramón , Fernández Miguel , Pérez Valentín , Garrido Joseba , Elguezabal Natalia
Published: January 2020

Paratuberculosis (PTB) is an enteric granulomatous disease caused by Mycobacterium avium subsp. paratuberculosis (MAP) that mainly affects ruminants. Current vaccines have shown to be cost–effective control reagents, although they are restricted due to cross-interference with bovine tuberculosis (bTB). Therefore, novel vaccination strategies are needed and this study is focused on evaluating alternative vaccination routes and their effect on the local immune response. The MAP oral challenge rabbit model was used to evaluate and compare an experimental inactivated MAP vaccine through oral (VOR) and intradermal (VID) routes. The VID group presented the highest proportion of animals with no visible lesions and the lowest proportion of animals with MAP positive tissues. Immunohistochemistry analysis revealed that the VID group presented a dominantly M1 polarized response indicating an ability to control MAP infection. In general, all vaccinated groups showed lower calprotectin levels compared to the non-vaccinated challenged group suggesting less active granulomatous lesions. The VID group showed some degree of skin test reactivity, whereas the same vaccine through oral administration was completely negative. These data show that PTB vaccination has an effect on macrophage polarization and that the route influences infection outcome and can also have an impact on bTB diagnosis. Future evaluation of new immunological products against mycobacterial diseases should consider assaying different vaccination routes.
2-D Characteristics of Wave Deformation Due to Wave-Current Interactions with Density Currents in an Estuary
Authors: Lee Woo-Dong , Mizutani Norimi , Hur Dong-Soo
Published: January 2020

In this study, numerical simulations were conducted in order to understand the role of wave-current interactions in wave deformation. The wave-current interaction mechanisms, wave reflection and energy loss due to currents, the effect of incident conditions on wave-current interactions, the advection-diffusion characteristics of saltwater, and the effect of density currents on wave-current interactions were discussed. In addition, the effect of saltwater–freshwater density on wave-current interactions was investigated under a hypopycnal flow field via numerical model testing. Turbulence was stronger under the influence of wave-current interactions than under the influence of waves alone, as wave-current interactions reduced wave energy, which led to decreases in wave height. This phenomenon was more prominent under shorter wave periods and higher current velocities. These results increase our understanding of hydrodynamic phenomena in estuaries in which saltwater–freshwater and wave-current pairs coexist.
Cost–Benefit Analysis of Leakage Reduction Methods in Water Supply Networks
Authors: Ahopelto Suvi , Vahala Riku
Published: January 2020

Reducing water loss from water supply systems is often regarded as one of the most important ways to improve the resource efficiency of water supply services. However, the costs and impacts of water loss reduction efforts need to be weighed against the benefits to define the optimal water loss target level. To this end, we conducted a cost–benefit analysis of three investment-based leakage reduction methods: district metering, pressure reduction, and pipe renovations. Furthermore, we conducted uncertainty and sensitivity analysis to determine the most relevant data for leakage analysis and policymaking on a national level. The results indicate that water loss management might not be directly cost-beneficial to utilities operating with moderate leakage levels. Neither leakage percentage nor the Infrastructure Leakage Index (ILI) were suitable for leakage target setting for the Finnish utilities. The costs of investing in district metering or renovations were the most influential factors in the sensitivity analysis, but the results showed that the estimated values were sufficiently accurate for assessing leakage policies.
Gender Perspective in Water Management: The Involvement of Women in Participatory Water Institutions of Eastern India
Authors: Khandker Varsha , Gandhi Vasant , Johnson Nicky
Published: January 2020

The paper examines the extent, nature, and factors affecting women’s involvement in participatory irrigation institutions of eastern India. Effective participatory water institutions are urgently needed to improve water management in eastern India, and a significant aspect of this is the involvement of women. There is inadequate representation, participation, and involvement of women in most water institutions. From the participatory and social point of view, this is a significant concern. The relevant data are obtained from the states of Assam and Bihar through a focused survey administered to 109 women in 30 water institutions, and a larger farmer-institutional survey covering 510 households and 51 water institutions. The research examines the extent and nature of the involvement of women in these institutions, as well as in farm decision-making, and the factors that prevent or foster their participation. Additionally, it examines the gender congruence in views regarding water institution activities and their performance, and the perceived benefits of formal involvement of women. The results show that their inclusion is very low (except required inclusion in Bihar), and the concerns of women are usually not being taken into account. Women are involved in farming and water management decisions jointly with men but not independently. Findings indicate that the views of women and men differ on many aspects, and so their inclusion is important. Responses indicate that if women participate formally in water user associations, it would enhance their social and economic standing, achieve greater gender balance, expand their awareness of water management, and contribute to better decision-making in the water institutions.
Will Automotive Be the Future of Mobility? Striving for Six Zeros
Authors: Rieck Frank , Machielse Kees , van Duin Ron
Published: January 2020

Will automotive be the future of mobility or will the motorcar era come to an end in the 21st century? Today, auto-mobility is still growing, but in the future, this will depend on its ability to adapt to the needs of modern society. Disruptive technologies like electrification, automation, and connectivity can make automotive more sustainable by striving for the Six Zero goals: Zero Emission, Zero Energy, Zero Congestion, Zero Accident, Zero Empty, and Zero Cost. These tempting goals can lead not only to a more sustainable ecology, but also to a new economy with more efficient use of the time and money needed for mobility. In this future mobility framework, this article describes the practice-oriented research of the Rotterdam University of Applied Sciences with its regional partners to achieve these goals.
Predicting Patient Wait Times in the Phlebotomy Unit
Authors: Orbatu Dilek , Yıldırım Oktay , Yaşar Eminullah , Şişman Ali Rıza , Sevinç Süleyman
Published: January 2020

Patients frequently complain of long waiting times in phlebotomy units. Patients try to
predict how long they will stay in the phlebotomy unit according to the number of patients in front of them. If it is not known how fast the queue is progressing, it is not possible to predict how long a patient will wait. The number of prior patients who will come to the phlebotomy unit is another important factor that changes the waiting time prediction.
We developed an artificial intelligence (AI)-based system that predicts patient waiting time in the phlebotomy unit. The system can predict the waiting time with high accuracy by considering all the variables that may affect the waiting time. In this study, the blood collection performance of phlebotomists, the duration of the phlebotomy in front of the patient, and the number of prior patients who could come to the phlebotomy unit was determined as the main parameters affecting the waiting time. For two months, actual wait times and predicted wait times were compared. The wait time for 95 percent of the patients was predicted with a variance of ± 2 minutes. An AI-based system helps patients make predictions with high accuracy, and patient satisfaction can be increased.
Exploratory Study on Variables of Social Cognitive Career Theory Influencing College Students’ Career Decision
Authors:   The Institute of Educational research Chonnam National University, Yon Kyu Jin
Published: January 2020

The purpose of the current study is to examine the effects of personal inputs (gender, year in college, GPAs, and anxiety), background affordances (parents’educational level, household income, and role model), cognitive-person variables (self-efficacy and outcome expectations) and contextual influences (career barriers) on college students’career decision level in Social Cognitive Career Theory. A total of 230 participants’survey responses were analyzed. The results of hierarchical multiple regression analyses indicated year in college, role model, and outcome expectations positively predicted career decision levels and career barriers negatively predicted career decision levels. Implications for career counselors, researchers, professors, and administrators were discussed.