bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary Inflammatory Index Score and Its Association with Body Weight, Blood Pressure, Lipid Profile, and Leptin in Indonesian Adults
Authors: Muhammad Harry Freitag Luglio , van Baak Marleen A. , Mariman Edwin C. , Sulistyoningrum Dian Caturini , Huriyati Emy , Lee Yi Yi , Wan Muda Wan Abdul Manan
Published: January 2019

It was previously reported that dietary intake is an important trigger for systemic inflammation and one of the lifestyle factors for the development of cardiovascular diseases. The aim of this study was to evaluate the association between Dietary Inflammatory Index (DII) score and body weight, blood pressure, lipid profile and leptin in an Indonesian population. This was a cross-sectional study conducted in 503 Indonesian adults. The DII score was calculated based on data of 30 nutrients and food components. Anthropometric profile, blood pressure, lipid profile, and leptin were measured. The association of these variables with the DII score was analyzed. The DII score was not associated with body weight, body mass index (BMI), body fat, waist circumference, hip circumference, systolic and diastolic blood pressure, triglycerides, and high-density lipoprotein (HDL) (both unadjusted and after adjustment for covariates). However, plasma leptin concentration was significantly associated with the DII score (B = 0.096, p = 0.020). Plasma leptin also increased significantly across tertiles of the DII score (ANCOVA, p = 0.031). This positive association between the DII score and plasma leptin concentration suggests a role for the inflammatory properties of the diet in regulating adipose tissue inflammation.
Evaluation of Prescription Adaptation Following Changes to A Provincial Drug Insurance Formulary
Authors: Pammett Robert T.
Published: January 2019

On 1 December 2016, British Columbia’s (BC) provincial drug insurance program changed which medications in certain classes would benefit under the insurance program in an attempt to reduce expenditure. As part of the modernization, HMG-CoA reductase inhibitors (Statins), Angiotensin converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARB), and dihydropyridine calcium channel blockers (CCB) were affected. Prescribers and pharmacists had six months to discuss the changes with patients, and change medications if deemed necessary. Purpose: To quantify the changes made to prescriptions and to adjust to the Modernized Reference Drug Program. Methods: A retrospective chart review was conducted at two clinics in Prince George, BC. Charts for patients that were prescribed any drugs in the affected classes were reviewed to determine if, and when, they had been changed, and by which health care professional. In December 2016, a clinical pharmacist, integrated within the study clinics, informed prescribers of the changes, and made patient-specific clinical notes within the charts. The notes described the changes and recommended alternative agents and appropriate dosing in order to assist the prescriber to have a conversation with the patient regarding the switch. Results: Out of 429 unique patients, 233 patients were prescribed a Statin, 229 patients an ACEI, 110 an ARB and, 83 a CCB. Sixty-five drug changes were indicated to reflect the modernization, and with guidance from a clinical pharmacist, nurse practitioners (NPs), and family physicians (FPs), 65% of these identified drugs were switched to reflect the modernization. Community pharmacists made no drug changes in the study sample, despite the prescriptive authority and compensation available to do so. Province-wide, approximately 21% to 33% of affected drugs were switched during the same time-frame. Direct collaboration between a clinical pharmacist, working alongside NPs and FPs, was more successful in optimizing these medications when compared to standard practice, or community pharmacists alone.
Dimensionless Numbers to Analyze Expansive Growth Processes
Authors: Ortega Joseph K. E.
Published: January 2019

Cells of algae, fungi, and plants have walls and exhibit expansive growth which can increase their volume by as much as 10,000 times. Expansive growth is central to their morphogenesis, development, and sensory responses to environmental stimuli. Equations describing the biophysical processes of the water uptake rate and the wall deformation rate have been derived, validated, and established. A significant amount of research provides insight into the molecular underpinnings of these processes. What is less well known are the relative magnitudes of these processes and how they compare during expansive growth and with walled cells from other species. Here, dimensionless numbers (Π parameters) are used to determine the magnitudes of the biophysical processes involved in the expansive growth rate of cells from algae (Chara corallina), fungi (Phycomyces blakesleeanus), and plants (Pisum satinis L.). It is found for all three species that the cell’s capability for the water uptake rate is larger than the wall plastic deformation rate and much larger than the wall elastic deformation rate. Also, the wall plastic deformation rates of all three species are of similar magnitude as their expansive growth rate even though the stress relaxation rates of their walls are very different. It is envisioned that dimensionless numbers can assist in determining how these biophysical processes change during development, morphogenesis, sensory responses, environmental stress, climate change, and after genetic modification.
Copper Metallopolymer Catalyst for the Electrocatalytic Hydrogen Evolution Reaction (HER)
Authors: Elmas Sait , Macdonald Thomas J. , Skinner William , Andersson Mats , Nann Thomas
Published: January 2019

Conjugated polymers with stabilizing coordination units for single-site catalytic centers are excellent candidates to minimize the use of expensive noble metal electrode materials. In this study, conjugated metallopolymer, POS[Cu], was synthesized and fully characterized by means of spectroscopical, electrochemical, and photophysical methods. The copper metallopolymer was found to be highly active for the electrocatalytic hydrogen generation (HER) in an aqueous solution at pH 7.4 and overpotentials at 300 mV vs. reversible hydrogen electrode (RHE). Compared to the platinum electrode, the obtained overpotential is only 100 mV higher. The photoelectrochemical tests revealed that the complexation of the conjugated polymer POS turned its intrinsically electron-accepting (p-type) properties into an electron-donor (n-type) with photocurrent responses ten times higher than the organic photoelectrode.
Synergistic Effects of Processing Additives and Thermal Annealing on Nanomorphology and Hole Mobility of Poly(3-hexylthiophene) Thin Films
Authors: Park Min Soo , Kim Felix Sunjoo
Published: January 2019

Control of the nanoscale molecular ordering and charge-carrier mobility of poly(3-hexylthiophene-2,5-diyl) (P3HT) was achieved by the combined use of processing additives and thermal annealing. Evaluation of four processing additives (1,8-octanedithiol (ODT), diphenyl ether (DPE), 1-chloronaphthalene (CN), and 1,8-diiodooctane (DIO), which are commonly used for the fabrication of organic solar cells, revealed that the nanoscale molecular ordering and, therefore, the charge-carrier mobility, are largely affected by the additives, as demonstrated by spectral absorption, X-ray diffraction, and atomic force microscopy. Thermal annealing selectively influenced the morphological changes, depending on the solubility of P3HT in the additive at high temperature. In the case of CN, in which P3HT can be dissolved at moderate temperature, significant molecular ordering was observed even without thermal annealing. For DIO, in which P3HT is only soluble at elevated temperature, the mobility reached 1.14 × 10−1 cm2 V−1 s−1 only after annealing. ODT and DPE were not effective as processing additives in a single-component P3HT. This study provides insight for designing the processing conditions to control the morphology and charge-transport properties of polymers.
Integrating Nano-Cu2O@ZrP into In Situ Polymerized Polyethylene Terephthalate (PET) Fibers with Enhanced Mechanical Properties and Antibacterial Activities
Authors: Zhou Jialiang , Fei Xiang , Li Congqi , Yu Senlong , Hu Zexu , Xiang Hengxue , Sun Bin , Zhu Meifang
Published: January 2019

The approach of in situ polymerization modification has proven to be an effective route for introducing functions for polyester materials. In this work, Cu2O@ZrP nanosheets with excellent dispersity and high antibacterial activity were integrated into in situ polymerized polyethylene terephthalate (PET) fibers, revealing an enhanced mechanical performance in comparison with the PET fibers fabricated directly via a traditional melt blending method. Additionally, such an in situ polymerized PET/Cu2O@ZrP fibers displayed highly enhanced mechanical properties; and great antibacterial activities against multi-types of bacterium, including S. aureus, E. coli and C. albicans. For the as-obtained two types of PET/Cu2O@ZrP fibers, we have detailed their molecular weight (detailed molecular weight) and dispersibility of nano-Cu2O@ZrP and fibers crystallinity was investigated by Gel chromatography (GPC), Scanning electron microscope (SEM), and X-ray diffractometer (XRD), respectively. The results showed that the aggregation of the nano-Cu2O@ZrP in the resultant PET matrix could be effectively prevented during its in situ polymerization process, hence we attribute its highly enhanced mechanical properties to its superior dispersion of nano-Cu2O@ZrP.
Synthesis and Effect of Structure on Swelling Properties of Hydrogels Based on High Methylated Pectin and Acrylic Polymers
Authors: Kowalski Grzegorz , Kijowska Karolina , Witczak Mariusz , Kuterasiński Łukasz , Łukasiewicz Marcin
Published: January 2019

The aim of the research was to develop new pectin-based hydrogels with excellent swelling properties. Superabsorbent hydrogels composed of high methylated pectin and partially neutralized poly(acrylic acid) was obtained by free radical polymerization in aqueous solution in the presence of crosslinking agent—N,N’-methylenebisacrylamide. The effect of crosslinker content and pectin to acrylic acid ratio on the swelling properties of hydrogels was investigated. In addition, the thermodynamic characteristic of hydrogels was obtained by DSC. Furthermore, the structure of pectin-based hydrogels was characterized by FTIR and GPC. It was also proved that poly(acrylic acid) is grafted on pectin particles. The results showed that introduction of small amount of pectin (up to 6.7 wt %) to poly(acrylic acid) hydrogel increase the swelling capacity, while further increasing of pectin ratio cause decrease of swelling.
Multi-Tubular Reactor for Hydrogen Production: CFD Thermal Design and Experimental Testing
Authors: Tapia Elvira , González-Pardo Aurelio , Iranzo Alfredo , Romero Manuel , González-Aguilar José , Vidal Alfonso , Martín-Betancourt Mariana , Rosa Felipe
Published: January 2019

This study presents the Computational Fluid Dynamics (CFD) thermal design and experimental tests results for a multi-tubular solar reactor for hydrogen production based on the ferrite thermochemical cycle in a pilot plant in the Plataforma Solar de Almería (PSA). The methodology followed for the solar reactor design is described, as well as the experimental tests carried out during the testing campaign and characterization of the reactor. The CFD model developed for the thermal design of the solar reactor has been validated against the experimental measurements, with a temperature error ranging from 1% to around 10% depending on the location within the reactor. The thermal balance in the reactor (cavity and tubes) has been also solved by the CFD model, showing a 7.9% thermal efficiency of the reactor. CFD results also show the percentage of reacting media inside the tubes which achieve the required temperature for the endothermic reaction process, with 90% of the ferrite pellets inside the tubes above the required temperature of 900 °C. The multi-tubular solar reactor designed with aid of CFD modelling and simulations has been built and operated successfully.
Acknowledgement to Reviewers of Processes in 2018
Authors:   Processes Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Acknowledgement to Reviewers of Publications in 2018
Authors:   Office Publications Editorial
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Repairing the Breach: Faith-Based Community Organizing to Dismantle Mass Incarceration
Authors: Levad Amy
Published: January 2019

Public awareness of the injustices of mass incarceration has grown significantly over the last decade. Many people have learned about mass incarceration in church contexts through book groups, study campaigns, and denominational statements. In recent years, faith-based community organizing (FBCO) networks have increasingly turned their attention to mass incarceration in light of the growing awareness of many Christian individuals, congregations, and denominations. Mass incarceration, however, presents three distinctive challenges to FBCO. First, dismantling mass incarceration requires overtly and conscientiously confronting white supremacy and advancing racial and ethnic equity; faith-based community organizers have avoided this work in the past for fear of dividing their base. Second, streams of Christian theology based in retributivism have provided justifications for increasingly punitive practices and policies, thus contributing to mass incarceration; FBCO networks must construct and uplift alternative theological streams to support alternative practices and policies. Finally, several practices and policies tied to mass incarceration deplete the political power of individuals, families, and communities most deeply impacted by it. Organizing against mass incarceration requires new strategies for building social capital and creating coalitions among groups who have been disenfranchised, marginalized, and undercounted by these practices and policies. Together, these challenges have required FBCO networks to adapt assumptions, strategies, and relationships that had previously been effective in addressing other issues, such as healthcare, employment, education, and transportation. Based on ethnographic fieldwork, this paper explores the insights, struggles, and innovations of ISAIAH, a network in Minnesota, as its members work to dismantle mass incarceration and confront its unique challenges.
“Mere” Christian Forgiveness: An Ecumenical Christian Conceptualization of Forgiveness through the Lens of Stress-And-Coping Theory
Authors: Worthington Everett L. , Rueger Sandra Yu , Davis Edward B. , Wortham Jennifer
Published: January 2019

Forgiveness is a central theme within the Christian faith, yet Christian traditions sometimes vary in how they understand and approach the forgiveness process. Nevertheless, in this paper, we present an ecumenical model of Christian forgiveness that highlights the essential components that are shared across most Christian traditions. Importantly, rather than using a theological lens to develop and describe this model, we have primarily used a psychological lens. Specifically, we have adopted stress-and-coping theory as the psychological framework for understanding a Christian conceptualization of forgiveness. We identify four types of forgiveness (divine forgiveness, self-forgiveness, person-to-person forgiveness, and organizational–societal forgiveness) and describe a Christian conceptualization of each one, filtered through the psychological perspective of stress-and-coping theory.
Moderate Southeast Asian Islamic Education as a Parent Culture in Deradicalization: Urgencies, Strategies, and Challenges
Authors: Susilo Sulistiyono , Dalimunthe Reza Pahlevi
Published: January 2019

Radicalization is a terminological conflation of the two meanings in the context of extreme beliefs or behaviors adopted by individuals or groups as a justification for the use of violence to achieve the objectives. Since radicalization primarily emphasises on, and departures from, the understanding and cognitive processes, the role of peaceful and moderate education in this case can be effectively utilized to serve as a considerably relevant means to prevent it. In addition, radicalization is also limited by the social, political, and economic contexts of a particular region, and combined with the degree of individual autonomy in the search for identity. Accordingly, the deradicalization efforts actually necessitate the consideration of the sociopolitical culture as the basis for policy makers. It is based on the consideration that the radicalization of Islam, even though strongly characterized by transnational movement, contains local elements leading to the radicalization as occasionally random and ununiformed violence in the Muslim world. The findings suggest some valuable strategies to deconstruct the idea of radicalization that can be implemented in several ways, including building and empowering local characterization of Indonesian education of Muslims in particular and of Southeast Asian in general, and reducing the Wahhabism extreme teachings and such highly irrational and ahistorical Arabization ideas and programs in Indonesian context.
Convolutional Neural Network Classification of Telematics Car Driving Data
Authors: Gao Guangyuan , Wüthrich Mario V.
Published: January 2019

The aim of this project is to analyze high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, deceleration, and changes of direction from this high-frequency GPS location data. Time series of this feature information allow us to appropriately allocate individual car driving trips to selected drivers using convolutional neural networks.
On-Board Georeferencing Using FPGA-Based Optimized Second-Order Polynomial Equation
Authors: Liu Dequan , Zhou Guoqing , Huang Jingjin , Zhang Rongting , Shu Lei , Zhou Xiang , Xin Chun Sheng
Published: January 2019

For real-time monitoring of natural disasters, such as fire, volcano, flood, landslide, and coastal inundation, highly-accurate georeferenced remotely sensed imagery is needed. Georeferenced imagery can be fused with geographic spatial data sets to provide geographic coordinates and positing for regions of interest. This paper proposes an on-board georeferencing method for remotely sensed imagery, which contains five modules: input data, coordinate transformation, bilinear interpolation, and output data. The experimental results demonstrate multiple benefits of the proposed method: (1) the computation speed using the proposed algorithm is 8 times faster than that using PC computer; (2) the resources of the field programmable gate array (FPGA) can meet the requirements of design. In the coordinate transformation scheme, 250,656 LUTs, 499,268 registers, and 388 DSP48s are used. Furthermore, 27,218 LUTs, 45,823 registers, 456 RAM/FIFO, and 267 DSP48s are used in the bilinear interpolation module; (3) the values of root mean square errors (RMSEs) are less than one pixel, and the other statistics, such as maximum error, minimum error, and mean error are less than one pixel; (4) the gray values of the georeferenced image when implemented using FPGA have the same accuracy as those implemented using MATLAB and Visual studio (C++), and have a very close accuracy implemented using ENVI software; and (5) the on-chip power consumption is 0.659 W. Therefore, it can be concluded that the proposed georeferencing method implemented using FPGA with second-order polynomial model and bilinear interpolation algorithm can achieve real-time geographic referencing for remotely sensed imagery.
Soil Moisture Monitoring Using Remote Sensing Data and a Stepwise-Cluster Prediction Model: The Case of Upper Blue Nile Basin, Ethiopia
Authors: Ayehu Getachew , Tadesse Tsegaye , Gessesse Berhan , Yigrem Yibeltal
Published: January 2019

In this study, a residual soil moisture prediction model was developed using the stepwise cluster analysis (SCA) and model prediction approach in the Upper Blue Nile basin. The SCA has the advantage of capturing the nonlinear relationships between remote sensing variables and volumetric soil moisture. The principle of SCA is to generate a set of prediction cluster trees based on a series of cutting and merging process according to a given statistical criterion. The proposed model incorporates the combinations of dual-polarized Sentinel-1 SAR data, normalized difference vegetation index (NDVI), and digital elevation model as input parameters. In this regard, two separate stepwise cluster models were developed using volumetric soil moisture obtained from automatic weather stations (AWS) and Noah model simulation as response variables. The performance of the SCA models have been verified for different significance levels (i.e., α = 0.01 , α = 0.05 , and α = 0.1 ). Thus, the AWS based SCA model with α = 0.05 was found to be an optimal model for predicting volumetric residual soil moisture, with correlation coefficient (r) values of 0. 95 and 0.87 and root mean square error (RMSE) of 0.032 and 0.097 m3/m3 during the training and testing periods, respectively. While in the case of the Noah SCA model an optimal prediction performance was observed when α value was set to 0.01, with r being 0.93 and 0.87 and RMSE of 0.043 and 0.058 m3/m3 using the training and testing datasets, respectively. In addition, our result indicated that the combined use of Sentinel-SAR data and ancillary remote sensing products such as NDVI could allow for better soil moisture prediction. Compared to the support vector regression (SVR) method, SCA shows better fitting and prediction accuracy of soil moisture. Generally, this study asserts that the SCA can be used as an alternative method for remote sensing based soil moisture predictions.
Handshake Sense Multiple Access Control for Cognitive Radio-Based IoT Networks
Authors: Shafiq Muhammad , Ahmad Maqbool , Khalil Afzal Muhammad , Ali Amjad , Irshad Azeem , Choi Jin-Ghoo
Published: January 2019

Internet-of-Things (IoT) enabling technologies such as ZigBee, WiFi, 6LowPAN, RFID, Machine-to-Machine, LTE-Advanced, etc. depend on the license-free Industrial Scientific and Medical (ISM) bands for the Internet. The proliferation of IoT devices is not only anticipated to create a huge amount of congestion in the near future, but even now the unlicensed spectrum is not enough in the ISM bands. Towards this end, Cognitive Radio (CR) technology can resolve the spectrum shortage issue since CR users can opportunistically exploit white spaces in licensed channels of the adjacent wireless systems. In CR networks, it is critical to coordinate spectrum access among Secondary Users (SUs) while protecting priority rights of Primary Users (PUs). Therein, SUs need to take good care of hidden PUs in order to avoid harmful interference. Further, a densely deployed CR network can compromise spectrum sensing quality and certainty of the results when a large number of SUs contends to access the same channel. Therefore, based on the vulnerable sensing results, SUs can cause interference to the PUs. In this paper, we first investigate the leading issues and then propose a novel Handshake Sense Multiple Access with Collision Avoidance (HSMA/CA) protocol for CR-based IoT networks. Our proposed HSMA/CA scheme resolves hidden primary terminal problem and maintains sufficient priority rights to PUs in a densely distributed network. In addition, we optimize the spectrum sensing period to maximize the system performance by maintaining peculiarities in the sensing operation like false alarm and misdetection. To evaluate the performance of HSMA/CA, we have analyzed the protocol through the Markov chain model in terms of throughput and verify its accuracy by simulations. Simulation results show that our scheme is suitable for non-collaborative densely deployed CR-based IoT networks.
Data-Driven Based Approach to Aid Parkinson’s Disease Diagnosis
Authors: Khoury Nicolas , Attal Ferhat , Amirat Yacine , Oukhellou Latifa , Mohammed Samer
Published: January 2019

This article presents a machine learning methodology for diagnosing Parkinson’s disease (PD) based on the use of vertical Ground Reaction Forces (vGRFs) data collected from the gait cycle. A classification engine assigns subjects to healthy or Parkinsonian classes. The diagnosis process involves four steps: data pre-processing, feature extraction and selection, data classification and performance evaluation. The selected features are used as inputs of each classifier. Feature selection is achieved through a wrapper approach established using the random forest algorithm. The proposed methodology uses both supervised classification methods including K-nearest neighbour (K-NN), decision tree (DT), random forest (RF), Naïve Bayes (NB), support vector machine (SVM) and unsupervised classification methods such as K-means and the Gaussian mixture model (GMM). To evaluate the effectiveness of the proposed methodology, an online dataset collected within three different studies is used. This data set includes vGRF measurements collected from eight force sensors placed under each foot of the subjects. Ninety-three patients suffering from Parkinson’s disease and 72 healthy subjects participated in the experiments. The obtained performances are compared with respect to various metrics including accuracy, precision, recall and F-measure. The classification performance evaluation is performed using the leave-one-out cross validation. The results demonstrate the ability of the proposed methodology to accurately differentiate between PD subjects and healthy subjects. For the purpose of validation, the proposed methodology is also evaluated with an additional dataset including subjects with neurodegenerative diseases (Amyotrophic Lateral Sclerosis (ALS) and Huntington’s disease (HD)). The obtained results show the effectiveness of the proposed methodology to discriminate PD subjects from subjects with other neurodegenerative diseases with a relatively high accuracy.
A Social Virtual Reality-Based Application for the Physical and Cognitive Training of the Elderly at Home
Authors: Arlati Sara , Colombo Vera , Spoladore Daniele , Greci Luca , Pedroli Elisa , Serino Silvia , Cipresso Pietro , Goulene Karine , Stramba-Badiale Marco , Riva Giuseppe , Gaggioli Andrea , Ferrigno Giancarlo , Sacco Marco
Published: January 2019

Frailty is a clinical condition affecting the elderly population which results in an increased risk of falls. Previous studies demonstrated that falls prevention programs are effective, but they suffer from low adherence, especially when subjects have to train unsupervised in their homes. To try to improve treatment adherence, virtual reality and social media have been proposed as promising strategies for the increase of users’ motivation and thus their willingness to practice. In the context of smart homes, this work presents SocialBike, a virtual reality-based application aimed at improving the clinical outcomes of older frail adults in their houses. Indeed, SocialBike is integrated in the “house of the future” framework and proposes a Dual Task training program in which the users are required to cycle on a stationary bike while recognizing target animals or objects appearing along the way. It also implements the possibility of training with other users, thus reducing the risk of social isolation. Within SocialBike, users can choose the multiplayer mode they prefer (i.e., collaborative or competitive), and are allowed to train following their own attitude. SocialBike’s validation, refinement, and business model are currently under development, and are briefly discussed as future works.
A Facile Electrochemical Sensor Labeled by Ferrocenoyl Cysteine Conjugate for the Detection of Nitrite in Pickle Juice
Authors: Feng Xiao-Zhen , Ferranco Annaleizle , Su Xiaorui , Chen Zhencheng , Jiang Zhiliang , Han Guo-Cheng
Published: January 2019

Simple and facile electrochemical sensors for nitrite detection were fabricated by directly depositing ferrocenoyl cysteine conjugates Fc[CO-Cys(Trt)-OMe]2 [Fc(Cys)2] or Fc[CO-Glu-Cys-Gly-OH] [Fc-ECG] on screen-printed electrodes (SPEs). The modified carbon electrodes were characterized by scanning electron microscopy (SEM), cyclic voltammetry (CV) and differential pulse voltammetry (DPV). Results indicated that Fc-ECG/SPE sensor showed enhanced current response and a lower overpotential than Fc(Cys)2/SPE sensor for nitrite detection. Optimal operating conditions were estimated for nitrite detection by DPV. The concentration of nitrite showed a good linear relationship with the current response in the range of 1.0–50 μmol·L−1 and with 0.3 μmol·L−1 as the concentration for limit of detection. There were no interferences from most common ions. The development of this electrochemical sensor was used for nitrite detection in pickled juice with a R.S.D. lower than 2.1% and average recovery lower than 101.5%, which indicated that disposable electrochemical sensor system can be applied for rapid and precise nitrite detection in foods.
Single Exhale Biomarker Breathalyzer
Authors: Karimi Yasha , Lin Yingkan , Jodhani Gagan , Stanaćević Milutin , Gouma Pelagia-Irene
Published: January 2019

A single exhale breathalyzer comprises a gas sensor that satisfies the following stringent conditions: high sensitivity to the target gas, high selectivity, stable response over extended period of time and fast response. Breathalyzer implementation includes a front-end circuit matching the sensitivity of the sensor that provides the readout of the sensor signal. We present here the characterization study of the response stability and response time of a selective Nitric Oxide (NO) sensor using designed data acquisition system that also serves as a foundation for the design of wireless handheld prototype. The experimental results with the described sensor and data acquisition system demonstrate stable response to NO concentration of 200 ppb over the period of two weeks. The experiments with different injection and retraction times of the sensor exposure to constant NO concentration show a fast response time of the sensor (on the order of 15 s) and the adequate recovery time (on the order of 3 min) demonstrating suitability for the single exhale breathalyzer.
An Improved Unauthorized Unmanned Aerial Vehicle Detection Algorithm Using Radiofrequency-Based Statistical Fingerprint Analysis
Authors: Yang Shengying , Qin Huibin , Liang Xiaolin , Gulliver Thomas Aaron
Published: January 2019

Unmanned aerial vehicles (UAVs) are now readily available worldwide and users can easily fly them remotely using smart controllers. This has created the problem of keeping unauthorized UAVs away from private or sensitive areas where they can be a personal or public threat. This paper proposes an improved radio frequency (RF)-based method to detect UAVs. The clutter (interference) is eliminated using a background filtering method. Then singular value decomposition (SVD) and average filtering are used to reduce the noise and improve the signal to noise ratio (SNR). Spectrum accumulation (SA) and statistical fingerprint analysis (SFA) are employed to provide two frequency estimates. These estimates are used to determine if a UAV is present in the detection environment. The data size is reduced using a region of interest (ROI), and this improves the system efficiency and improves azimuth estimation accuracy. Detection results are obtained using real UAV RF signals obtained experimentally which show that the proposed method is more effective than other well-known detection algorithms. The recognition rate with this method is close to 100% within a distance of 2.4 km and greater than 90% within a distance of 3 km. Further, multiple UAVs can be detected accurately using the proposed method.
Reconstruction of 3D Pavement Texture on Handling Dropouts and Spikes Using Multiple Data Processing Methods
Authors: Dong Niya , Prozzi Jorge A. , Ni Fujian
Published: January 2019

Tire–pavement interactions, like friction and rolling resistance, are significantly influenced by pavement macro-texture and micro-texture. Accurate texture measurement at the micro-texture level is vital to achieve the desired level of safety, comfort, and sustainability of the pavement. However, the existence of dropouts and spikes in the collected data is still inevitable based on current laser devices, which leads to erroneous texture characterization. This study utilized an advanced laser sensor to measure three-dimensional (3D) pavement texture at the micro-level at a given speed. Using a proposed interpolation method, the dropout areas in the raw measurements were filled up. Butterworth’s high-pass and low-pass filters were applied to separate two texture components from the profile. Based on a statistical analysis for the micro-texture amplitude, an appropriate threshold was determined in order to identify the spikes. A three-step-spike-removal method was proposed and found to be effective in clearing the spikes. The 3D pavement profiles were finally reconstructed without dropouts and spikes. Mean profile depth (MPD) was calculated with different baselines. It was found that the presence of spikes leads to a greater MPD value and the MPD is sensitive to the baseline length. A shorter baseline is recommended to mitigate the impact of spikes on the accuracy of the MPD.
An Investigation of the Use of Language, Social Identity and Multicultural Values for Nation-Building in Malaysian Outdoor Advertising
Authors: Ahmad Tajuddin Siti Nor Amalina , Zulkepli Noraini
Published: January 2019

The mass media in the form of advertising is extensively employed in the process of nation-building in Malaysia. Advertising has been used as an important tool for educating the public about State issues, ensuring diverse cultures are equally represented and the multicultural values are emphasized to the fullest. The objective of the present study is to investigate how outdoor advertising, particularly billboards, promotes the language, social identity, and multicultural values of Malaysian society for nation-building. In Malaysia, the extensive use of advertisements has been argued as one of the most powerful mechanisms to enhance Malaysian identity, foster interactions and thus contribute to the process of nation-building even though it is portrayed in a banal and routine way. To achieve its objective, this paper utilizes semiotic methodology to examine 11 billboards to understand the relationships between texts and visuals that communicate messages to the public. The findings revealed that the billboards do not only communicate pro-social messages, but also reflect the language, social identity and multicultural values of Malaysian society towards nation-building. This study expands the work of outdoor advertising within the Malaysian society and contributes to Semiotic Analysis by examining textual-visual elements of billboards.
Acknowledgement to Reviewers of Stats in 2018
Authors:   Stats Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Does Social Network Sentiment Influence S&P 500 Environmental & Socially Responsible Index?
Authors: López-Cabarcos M. Ángeles , Pérez-Pico Ada M. , López-Pérez M. Luisa
Published: January 2019

The influence of social network sentiment on stock market indices and companies has been proven in several studies. However, the influence of social network sentiment on sustainability indices and sustainable companies has not been analyzed so far. Therefore, this study analyzed the influence of social network sentiment on sustainability indices (S&P 500 Environmental & Socially Responsible Index) and focused on variations of this influence on sustainable and non-sustainable companies, namely, in companies included in the Information Technology sector. To this end, two methodologies were used: GARCH (1,1) models and logit-probit models. The results showed that social network sentiment influences S&P 500 Environmental & Socially Responsible Index’s volatility; this influence was greater than the influence of social network sentiment when considering the S&P 500 Index. Additionally, the results showed that social network sentiment influences sustainable companies’ returns but had no effect on unsustainable companies’ returns. These results highlighted the importance of managing the companies’ profiles in social networks and their corporate image in general, because investors will consider these aspects to design their investment strategies.
Web-Based Recommendation System for Smart Tourism: Multiagent Technology
Authors: Hassannia Raheleh , Vatankhah Barenji Ali , Li Zhi , Alipour Habib
Published: January 2019

The purpose of the study is to design and develop a recommended system based on agent and web technologies, which utilizes a hybrid recommendation filtering for the smart tourism industry. A hybrid recommendation system based on agent technology is designed by considering the online communication with other sectors in the tourism industry, such as the tourism supply chain, agency etc. However, online communication between the sectors via agents is designed and developed based on the contract net protocol. Furthermore, the design system is developed on the java agent development framework and implemented as a web application. Case study-based results considering two scenarios involving 100 customers illustrated that the proposed web application improves the rate of the recommendation for the customers. In the first scenario without disturbances, this rate was improved by 20% and the second scenario with disturbances yielded a 30% rate of acceptable recommendation. In addition, based on the second scenario, real time data communication on the system occurred, thus the proposed system supported real time data communication.
The Significance of the Adaptive Thermal Comfort Limits on the Air-Conditioning Loads in a Temperate Climate
Authors: Albatayneh Aiman , Alterman Dariusz , Page Adrian , Moghtaderi Behdad
Published: January 2019

The building industry is regarded a major contributor to climate change as energy consumption from buildings accounts for 40% of the total energy. The types of thermal comfort models used to predict the heating and cooling loads are critical to save energy in operative buildings and reduce greenhouse gas emissions (GHG). In this research, the internal air temperatures were recorded for over one year under the free floating mode with no heating or cooling, then the number of hours required for heating or cooling were calculated based on fixed sets of operative temperatures (18 °C–24 °C) and the adaptive thermal comfort model to estimate the number of hours per year required for cooling and heating to sustain the occupants’ thermal comfort for four full-scale housing test modules at the campus of the University of Newcastle, Australia. The adaptive thermal comfort model significantly reduced the time necessary for mechanical cooling and heating by more than half when compared with the constant thermostat setting used by the air-conditioning systems installed on the site. It was found that the air-conditioning system with operational temperature setups using the adaptive thermal comfort model at 80% acceptability limits required almost half the operating energy when compared with fixed sets of operating temperatures. This can be achieved by applying a broader range of acceptable temperature limits and using techniques that require minimal energy to sustain the occupants’ thermal comfort.
Positive Relational Management for Sustainable Development: Beyond Personality Traits—The Contribution of Emotional Intelligence
Authors: Di Fabio Annamaria , Saklofske Donald H.
Published: January 2019

Positive relationships are of major importance in our personal and working lives for promoting well-being, and fostering healthy and sustainable organizations. The research literature suggests that emotional intelligence is a key factor in promoting and maintaining positive relationships. We examined the association between trait emotional intelligence and positive relational management in Italian workers, controlling for the effects of personality traits. Participants were administered the Big Five Questionnaire (BFQ), the Trait Emotional Intelligence Questionnaire Short Form (TEIQue-SF) and the Positive Relational Management Scale (PRMS). Hierarchical regression analyses showed that trait emotional intelligence explained an additional 14–16% of the variance beyond personality traits in relation to positive relational management in workers. These results underscore the relationship between trait emotional intelligence and positive relational management, offering new opportunities for promoting both personal well-being and healthy and sustainable organizations.
Mitigation Effect of Carbon Emission Tax in Dairy Farming: An Empirical Study of Heilongjiang Province in China
Authors: Shi Shuai , Jing Yu , Li Cuixia
Published: January 2019

From a production perspective, this study evaluates the mitigation effect of a carbon emission tax (CET) on dairy farming in Heilongjiang Province. The marginal analysis method is used in the paper. The total cost and operation cost are respectively considered in the long and short run. We have five types of CETs and four scales of dairy farming. A CET is levied on milk, the main dairy product. We investigate the marginal costs and benefits of different scales and simulate the exit rates and mitigations. We conclude that 30 yuan/t CO2e is the suitable CET, leading to the mitigation of 0.79% with the cost of 0.17% revenue loss. The heterogeneity of marginal cost (MC) of each scale is a major factor affecting the exit rate, rather than the average MC. We also find there is a larger mitigation response in long run, and economies of scale are effective in resisting the CET. The revenue of CET can subsidize low-carbon dairy farms and silage, which will promote biogas digester engineering and harmless treatment of manure.
Social Effects of Economic Crisis: Risk of Exclusion. An Overview of the European Context
Authors: Novo-Corti Isabel , Țîrcă Diana-Mihaela , Ziolo Magdalena , Picatoste Xose
Published: January 2019

Sustainability is a complex concept. It only can be achieved from a global perspective, where social, economic and environmental issues are all key factors for achieving the goal. This paper is focused on the importance of social sustainability and, as a consequence, the importance of avoiding each and everyone’s risk of poverty and exclusion as due to the recent crisis effects. Nevertheless, this crisis resulted in higher inequalities and put a lot of people at risk of poverty, even in “developed” countries. Through a statistical and econometric analysis, some of the key factors to which the European Union should aim to avoid unsustainable scenarios are analysed. A regression, factorial and cluster analysis is carried out and this leads to conclude that the labour market is key in promoting economic policies in order to achieve social sustainability.
Distribution of Cd and Cu Fractions in Chinese Soils and Their Relationships with Soil pH: A Meta-Analysis
Authors: Ning Yinzhong , Zhang Xinmu , Li Binzhe , Wang Yajing , Guo Jingheng
Published: January 2019

Soil contamination by potentially toxic metals (PTMs) has become a public concern in China. However, the distribution and controlling factors of soil PTM fractions remain largely unknown, limiting our ability to assess their health risks and thus to make sound controlling polices. Here, we investigate the fraction distribution of cadmium (Cd) and copper (Cu) in Chinese soils and their relationships with soil pH, based on a national meta-analysis of 163 published literatures. Exchangeable Cd in southern China accounted for 19.50 ± 14.97% of total Cd, significantly (p < 0.01) higher than the corresponding 13.42 ± 6.95% in northern China. Potentially available fractions constituted about 60% of total Cd at the national scale. By contrast, about half of soil Cu existed in unavailable residual fraction. Phytoavailable (i.e., exchangeable) fraction accounted for only 2.71 ± 1.65% and 2.54 ± 1.58% of total Cu in northern and southern China, respectively. Percentages of exchangeable Cd and Cu were negatively correlated (p < 0.01) with soil pH, while potentially available fractions increased significantly (p < 0.05) with soil pH. Our results provide the first national assessment of Cd and Cu fraction distribution and their responses to soil pH variations, highlighting the necessity to consider their fraction distribution and soil properties when assessing the health risks of soil PTM contamination in China.
How are Anti-Air Pollution Policies Implemented? A Network Analysis of Campaign-Style Enforcement in China
Authors: Meng Fanrong , Chen Zitao , Wu Jiannan
Published: January 2019

Haze pollution has become one of the most important environment problems in China, raising increasing serious public health concerns. When carried out through campaign-style enforcement drives, the nation’s anti-air pollution policy and its implementation require all-levels of government to take measures to improve the air quality in a certain period. In this study, Xi’an, a city in northwest China, where serious haze occurs frequently, was chosen as the research sample. Based on a social network analysis of the Anti-pollution and Anti-haze Work Scheme of Xi’an for 2014 and 2015 as well as in-depth interviews with enforcement officials, we studied the attributes of the enforcement network, including the actors’ respective tasks, the network’s structure, and the ‘centrality’ of the network. Compared to 2014, the goals of the 2015 scheme were clearer and more challenging, with a larger number of specific tasks and tighter time limits. The structure of the enforcement network became flatter, with a ‘horizontal’ management arrangement that involved fewer actors. The core actors were shifted to the more authoritative departments, reflecting the reality that the campaign-style enforcement network structure had been adjusted toward the regulatory hierarchy system and routing administration. The results reveal that the implementation gap was narrowed by clearer and more specific roles and tasks, a simplified, flatter organizational network structure, greater decentralization of authority and responsibility to local departments, and more harmonious coordination among those departments with the most powerful leading actors. This study provides managers with an insight into the external and organizational factors involved in enhancing the effectiveness of anti-air pollution policy implementation.