bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of E-Textile Techniques and Materials for 3D Gesture Sensor with Boosted Electrode Design
Authors: Ferri Josue , Llinares Llopis Raúl , Martinez Gabriel , Lidon Roger José Vicente , Garcia-Breijo Eduardo
Published: April 2020

There is an interest in new wearable solutions that can be directly worn on the curved human body or integrated into daily objects. Textiles offer properties that are suitable to be used as holders for electronics or sensors components. Many sensing technologies have been explored considering textiles substrates in combination with conductive materials in the last years. In this work, a novel solution of a gesture recognition touchless sensor is implemented with satisfactory results. Moreover, three manufacturing techniques have been considered as alternatives: screen-printing with conductive ink, embroidery with conductive thread and thermosealing with conductive fabric. The main critical parameters have been analyzed for each prototype including the sensitivity of the sensor, which is an important and specific parameter of this type of sensor. In addition, user validation has been performed, testing several gestures with different subjects. During the tests carried out, flick gestures obtained detection rates from 79% to 89% on average. Finally, in order to evaluate the stability and strength of the solutions, some tests have been performed to assess environmental variations and washability deteriorations. The obtained results are satisfactory regarding temperature and humidity variations. The washability tests revealed that, except for the screen-printing prototype, the sensors can be washed with minimum degradation.
Applications of Smart Textiles in Post-Stroke Rehabilitation
Authors: Korzeniewska Ewa , Krawczyk Andrzej , Mróz Józef , Wyszyńska Elżbieta , Zawiślak Rafał
Published: April 2020

Stroke is a disease affecting a large part of our society. According to WHO data, it is the second world’s biggest killer, accounting for near six million deaths in 2016 and it is about 30% of the total number of strokes per year. Other patients affected by such a disease should be rehabilitated as soon as possible. As a result of this phenomenon, paresis may occur. Among the devices available on the market there are many rehabilitation robots, but the method of electrostimulation can be used. The authors focused their attention on electrostimulation and commercially available therapies. Using this method, application to people with large hand muscle contracture is difficult. The authors of the work present a solution dedicated to exactly such people. A solution of textronic sensors manufactured on a textile substrate using the technology of physical vapor deposition is presented in the article. As a result of the conducted research, an electroconductive structure was obtained with a low surface resistance value of 1 Ω/□ and high flexibility. It can alternatively be used in hand rehabilitation for electrostimulation of fingertips. The solution is dedicated to people with high hands spasticity for whom it is impossible to put on a rehabilitation glove.
Oven-Controlled MEMS Oscillator with Integrated Micro-Evaporation Trimming
Authors: Pei Binbin , Sun Ke , Yang Heng , Ye Chaozhan , Zhong Peng , Yu Tingting , Li Xinxin
Published: April 2020

This study reports an oven-controlled microelectromechanical systems oscillator with integrated micro-evaporation trimming that achieves frequency stability over the industrial temperature range and permanent frequency trimming after vacuum packaging. The length-extensional-mode resonator is micro-oven controlled and doped degenerately with phosphorous to achieve a frequency instability of ±2.6 parts per million (ppm) in a temperature range of −40 to 85 °C. The micro-evaporators are bonded to the resonator, integrated face-to-face, and encapsulated in vacuum. During trimming, the micro-evaporators are heated electrically, and the aluminum layers on their surfaces are evaporated and deposited on the surface of the resonator that trims the resonant frequency of the resonator permanently. The impact of the frequency trimming on the temperature stability is very small. The temperature drift increases from ±2.6 ppm within the industrial temperature range before trimming to ±3.3 ppm after a permanent trimming of −426 ppm based on the local evaporation of Al. The trimming rate can be controlled by electric power. A resonator is coarse-trimmed by approximately −807 ppm with an evaporation power of 960 mW for 0.5 h, and fine-trimmed by approximately −815 ppm with an evaporation power of 456 mW for 1 h. Though the Q-factor decreases after trimming, a Q-factor of 304,240 is achieved after the trimming of −1442 ppm.
Human Interaction Smart Subsystem—Extending Speech-Based Human-Robot Interaction Systems with an Implementation of External Smart Sensors
Authors: Podpora Michal , Gardecki Arkadiusz , Beniak Ryszard , Klin Bartlomiej , Vicario Jose Lopez , Kawala-Sterniuk Aleksandra
Published: April 2020

This paper presents a more detailed concept of Human-Robot Interaction systems architecture. One of the main differences between the proposed architecture and other ones is the methodology of information acquisition regarding the robot’s interlocutor. In order to obtain as much information as possible before the actual interaction took place, a custom Internet-of-Things-based sensor subsystems connected to Smart Infrastructure was designed and implemented, in order to support the interlocutor identification and acquisition of initial interaction parameters. The Artificial Intelligence interaction framework of the developed robotic system (including humanoid Pepper with its sensors and actuators, additional local, remote and cloud computing services) is being extended with the use of custom external subsystems for additional knowledge acquisition: device-based human identification, visual identification and audio-based interlocutor localization subsystems. These subsystems were deeply introduced and evaluated in this paper, presenting the benefits of integrating them into the robotic interaction system. In this paper a more detailed analysis of one of the external subsystems—Bluetooth Human Identification Smart Subsystem—was also included. The idea, use case, and a prototype, integration of elements of Smart Infrastructure systems and the prototype implementation were performed in a small front office of the Weegree company as a decent test-bed application area.
ACD: An Adaptable Approach for RFID Cloning Attack Detection
Authors: Huang Weiqing , Zhang Yanfang , Feng Yue
Published: April 2020

With the rapid development of the internet of things, radio frequency identification (RFID) technology plays an important role in various fields. However, RFID systems are vulnerable to cloning attacks. This is the fabrication of one or more replicas of a genuine tag, which behave exactly as a genuine tag and fool the reader to gain legal authorization, leading to potential financial loss or reputation damage. Many advanced solutions have been proposed to combat cloning attacks, but they require extra hardware resources, or they cannot detect a clone tag in time. In this article, we make a fresh attempt to counterattack tag cloning based on spatiotemporal collisions. We propose adaptable clone detection (ACD), which can intuitively and accurately display the positions of abnormal tags in real time. It uses commercial off-the-shelf (COTS) RFID devices without extra hardware resources. We evaluate its performance in practice, and the results confirm its success at detecting cloning attacks. The average accuracy can reach 98.7%, and the recall rate can reach 96%. Extensive experiments show that it can adapt to a variety of RFID application scenarios.
A Smart Waste Management Solution Geared towards Citizens
Authors: Pardini Kellow , Rodrigues Joel J.P.C. , Diallo Ousmane , Das Ashok Kumar , de Albuquerque Victor Hugo C. , Kozlov Sergei A.
Published: April 2020

Global industry is undergoing major transformations with the genesis of a new paradigm known as the Internet of Things (IoT) with its underlying technologies. Many company leaders are investing more effort and money in transforming their services to capitalize on the benefits provided by the IoT. Thereby, the decision makers in public waste management do not want to be outdone, and it is challenging to provide an efficient and real-time waste management system. This paper proposes a solution (hardware, software, and communications) that aims to optimize waste management and include a citizen in the process. The system follows an IoT-based approach where the discarded waste from the smart bin is continuously monitored by sensors that inform the filling level of each compartment, in real-time. These data are stored and processed in an IoT middleware providing information for collection with optimized routes and generating important statistical data for monitoring the waste collection accurately in terms of resource management and the provided services for the community. Citizens can easily access information about the public waste bins through the Web or a mobile application. The creation of the real prototype of the smart container, the development of the waste management application and a real-scale experiment use case for evaluation, demonstration, and validation show that the proposed system can efficiently change the way people deal with their garbage and optimize economic and material resources.
A Spatiotemporal Convolutional Network for Multi-Behavior Recognition of Pigs
Authors: Li Dan , Zhang Kaifeng , Li Zhenbo , Chen Yifei
Published: April 2020

The statistical data of different kinds of behaviors of pigs can reflect their health status. However, the traditional behavior statistics of pigs were obtained and then recorded from the videos through human eyes. In order to reduce labor and time consumption, this paper proposed a pig behavior recognition network with a spatiotemporal convolutional network based on the SlowFast network architecture for behavior classification of five categories. Firstly, a pig behavior recognition video dataset (PBVD-5) was built by cutting short clips from 3-month non-stop shooting videos, which was composed of five categories of pig’s behavior: feeding, lying, motoring, scratching and mounting. Subsequently, a SlowFast network based spatiotemporal convolutional network for the pig’s multi-behavior recognition (PMB-SCN) was proposed. The results of the networks with variant architectures of the PMB-SCN were implemented and the optimal architecture was compared with the state-of-the-art single stream 3D convolutional network in our dataset. Our 3D pig behavior recognition network showed a top-1 accuracy of 97.63% and a views accuracy of 96.35% on the test set of PBVD and a top-1 accuracy of 91.87% and a views accuracy of 84.47% on a new test set collected from a completely different pigsty. The experimental results showed that this network provided remarkable ability of generalization and possibility for the subsequent pig detection and behavior recognition simultaneously.
Uncertainty-Aware Visual Perception System for Outdoor Navigation of the Visually Challenged
Authors: Dimas George , Diamantis Dimitris E. , Kalozoumis Panagiotis , Iakovidis Dimitris K.
Published: April 2020

Every day, visually challenged people (VCP) face mobility restrictions and accessibility limitations. A short walk to a nearby destination, which for other individuals is taken for granted, becomes a challenge. To tackle this problem, we propose a novel visual perception system for outdoor navigation that can be evolved into an everyday visual aid for VCP. The proposed methodology is integrated in a wearable visual perception system (VPS). The proposed approach efficiently incorporates deep learning, object recognition models, along with an obstacle detection methodology based on human eye fixation prediction using Generative Adversarial Networks. An uncertainty-aware modeling of the obstacle risk assessment and spatial localization has been employed, following a fuzzy logic approach, for robust obstacle detection. The above combination can translate the position and the type of detected obstacles into descriptive linguistic expressions, allowing the users to easily understand their location in the environment and avoid them. The performance and capabilities of the proposed method are investigated in the context of safe navigation of VCP in outdoor environments of cultural interest through obstacle recognition and detection. Additionally, a comparison between the proposed system and relevant state-of-the-art systems for the safe navigation of VCP, focused on design and user-requirements satisfaction, is performed.
Design and Evaluation of Flooding-Based Location Service in Vehicular Ad Hoc Networks
Authors: Mühlethaler Paul , Renault Éric , Boumerdassi Selma
Published: April 2020

Location-based routing protocols for vehicular ad hoc networks (VANETs) use location information to determine routing decisions. This information is provided by a location service that is queried by nodes in order to properly forward packets to communication partners. This paper presents the semiflooding location service, a proactive flooding-based location service that drastically reduces the number of update packets sent over the network compared to traditional flooding-based location services. This goal is achieved by each node partially forwarding location information. We present both deterministic and probabilistic approaches for this algorithm, which remains very simple. A mathematical model is proposed to show the effectiveness of this solution. The cases of homogeneous 1D, 2D, and 3D networks were studied for both deterministic and probabilistic forwarding decisions. We compare our algorithm with simple flooding and with the multipoint-relay (MPR) flooding of the optimized-link-state-routing (OLSR) protocol, and we show that our algorithm, despite being very simple, has excellent scalability properties. The mean number of generated messages ranges with the mean number of the neighbors of one random network node.
A Local Neighborhood Robust Fuzzy Clustering Image Segmentation Algorithm Based on an Adaptive Feature Selection Gaussian Mixture Model
Authors: Ren Hang , Hu Taotao
Published: April 2020

Since the fuzzy local information C-means (FLICM) segmentation algorithm cannot take into account the impact of different features on clustering segmentation results, a local fuzzy clustering segmentation algorithm based on a feature selection Gaussian mixture model was proposed. First, the constraints of the membership degree on the spatial distance were added to the local information function. Second, the feature saliency was introduced into the objective function. By using the Lagrange multiplier method, the optimal expression of the objective function was solved. Neighborhood weighting information was added to the iteration expression of the classification membership degree to obtain a local feature selection based on feature selection. Each of the improved FLICM algorithm, the fuzzy C-means with spatial constraints (FCM_S) algorithm, and the original FLICM algorithm were then used to cluster and segment the interference images of Gaussian noise, salt-and-pepper noise, multiplicative noise, and mixed noise. The performances of the peak signal-to-noise ratio and error rate of the segmentation results were compared with each other. At the same time, the iteration time and number of iterations used to converge the objective function of the algorithm were compared. In summary, the improved algorithm significantly improved the ability of image noise suppression under strong noise interference, improved the efficiency of operation, facilitated remote sensing image capture under strong noise interference, and promoted the development of a robust anti-noise fuzzy clustering algorithm.
Indoor Test System for Liquid CO2 Phase Change Shock Wave Pressure with PVDF Sensors
Authors: Huang Xing , Li Qiyue , Wei Xin’ao , Yang Xiaoxiao , Luo Dayou , Zeng Haideng , Wang Hongwei
Published: April 2020

Liquid carbon dioxide phase change fracturing technology (LCPCFT) has been widely used in engineering blasting due to the advantage of no flames, and no toxic and harmful gas. However, few studies have been conducted on the acquisition of shock wave pressure and its loading characteristics, which are key parameters in fracturing. Referring to the CO2 in-situ fracturing technology, an indoor test system for shock wave pressure generated during LCPCFT has been built, with a protected polyvinylidene fluoride (PVDF) piezoelectric sensor. Then three verification experiments with different radial distances between the fracturing tube and test points were carried out on the test system, and in each experiment, four PVDF sensors as four test points were arranged with different axial distance from the detonating point to test the pressure distribution. The experimental results show that when the radial distance between the fracturing tube and test points is not too large (≤345 mm), the pressure generated during LCPCFT is approximately uniformly distributed within the axial length of the fracturing tube, but when it is relatively large (≈895 mm), the results between different test points are in a certain degree of dispersion. And finally, this paper uses the intraclass correlation coefficient (ICC) and coefficient of variation (CV) of peak pressure and impulse to process the test results to evaluate the reliability and stability of the test system. Evaluation results show that the test results are in good consistency. The test system in this paper has good stability and high reliability. The test system provides a useful tool for accurately obtaining the shock wave pressure, which is helpful for further research on LCPCFT.
A Vision-Based Method for Determining Aircraft State during Spin Recovery
Authors: Kapuscinski Tomasz , Szczerba Piotr , Rogalski Tomasz , Rzucidlo Pawel , Szczerba Zygmunt
Published: April 2020

This article proposes a vision-based method of determining in which of the three states, defined in the spin recovery process, is an aircraft. The correct identification of this state is necessary to make the right decisions during the spin recovery maneuver. The proposed solution employs a keypoints displacements analysis in consecutive frames taken from the on-board camera. The idea of voting on the temporary location of the rotation axis and dominant displacement direction was used. The decision about the state is made based on a proposed set of rules employing the histogram spread measure. To validate the method, experiments on flight simulator videos, recorded at varying altitudes and in different lighting, background, and visibility conditions, were carried out. For the selected conditions, the first flight tests were also performed. Qualitative and quantitative assessments were conducted using a multimedia data annotation tool and the Jaccard index, respectively. The proposed approach could be the basis for creating a solution supporting the pilot in the process of aircraft spin recovery and, in the future, the development of an autonomous method.
Adaptive Smoothness Constraint Ionospheric Tomography Algorithm
Authors: Wen Debao , Mei Dengkui , Du Yanan
Published: April 2020

Ionospheric tomography reconstruction based on global navigation satellite system observations is usually an ill-posed problem. To resolve it, an adaptive smoothness constraint ionospheric tomography algorithm is proposed in this work. The new algorithm performs an adaptive adjustment for the constrained weight coefficients of the tomography system. The computational efficiency and the reconstructed quality of ionospheric imaging are improved by using the new algorithm. A numerical simulation experiment was conducted in order to validate the feasibility and superiority of the algorithm. The statistical results of the reconstructed errors and the comparisons of ionospheric profiles confirmed the superiority of the new algorithm. Finally, the new algorithm was successfully applied to reconstruct three-dimensional ionospheric images under geomagnetic quiet and geomagnetic disturbance conditions over Hunan province. The tomographic results are reasonable and consistent with the general behavior of the ionosphere. The positive and negative phase storm effects are found during geomagnetic storm occurrence.
KickStat: A Coin-Sized Potentiostat for High-Resolution Electrochemical Analysis
Authors: Hoilett Orlando S. , Walker Jenna F. , Balash Bethany M. , Jaras Nicholas J. , Boppana Sriram , Linnes Jacqueline C.
Published: April 2020

The demand for wearable and point-of-care devices has led to an increase in electrochemical sensor development to measure an ever-increasing array of biological molecules. In order to move from the benchtop to truly portable devices, the development of new biosensors requires miniaturized instrumentation capable of making highly sensitive amperometric measurements. To meet this demand, we have developed KickStat, a miniaturized potentiostat that combines the small size of the integrated Texas Instruments LMP91000 potentiostat chip (Texas Instruments, Dallas, TX, USA) with the processing power of the ARM Cortex-M0+ SAMD21 microcontroller (Microchip Technology, Chandler, AZ, USA) on a custom-designed 21.6 mm by 20.3 mm circuit board. By incorporating onboard signal processing via the SAMD21, we achieve 1 mV voltage increment resolution and an instrumental limit of detection of 4.5 nA in a coin-sized form factor. This elegant engineering solution allows for high-resolution electrochemical analysis without requiring extensive circuitry. We measured the faradaic current of an anti-cocaine aptamer using cyclic voltammetry and square wave voltammetry and demonstrated that KickStat’s response was within 0.6% of a high-end benchtop potentiostat. To further support others in electrochemical biosensors development, we have made KickStat’s design and firmware available in an online GitHub repository.
Use of Spectroscopic Techniques for a Rapid and Non-Destructive Monitoring of Thermal Treatments and Storage Time of Sous-Vide Cooked Cod Fillets
Authors: Hassoun Abdo , Cropotova Janna , Rustad Turid , Heia Karsten , Lindberg Stein-Kato , Nilsen Heidi
Published: April 2020

In this work, the potential of spectroscopic techniques was studied to investigate heat-induced changes occurring during the application of thermal treatments on cod (Gadus morhua L.) fillets. Vacuum-packed samples were thermally treated in a water bath at 50, 60, 70 and 80 °C for 5 and 10 min, and further stored for one, four, and eight days at 4 ± 1 °C before analysis. Several traditional (including cooking loss, drip loss, texture, protein solubility, protein oxidation, and color) and spectroscopic (fluorescence and diffuse reflectance hyperspectral imaging) measurements were conducted on the same samples. The results showed a decrease in fluorescence intensity with increasing cooking temperature and storage time, while the impact of cooking time was only noticeable at low temperatures. Diffuse reflectance data exhibited a decrease in absorbance, possibly as a result of protein denaturation and increased scattering at higher cooking temperatures. Both fluorescence and diffuse reflectance data were highly correlated with color parameters, whereas moderate correlations were observed with most other traditional parameters. Support vector machine models performed better than partial least square ones for both classification of cod samples cooked at different temperatures and in prediction of the cooking temperature. The best classification result was obtained on fluorescence data, achieving an accuracy of 92.5%, while the prediction models resulted in a root mean square error of prediction of cooking temperature lower than 5 °C. Overall, the classification and prediction models showed good results, indicating that spectroscopic techniques, especially fluorescence hyperspectral imaging, have a high potential for monitoring thermal treatments in cod fillets.
Performance Evaluation and Compensation Method of Trigger Probes in Measurement Based on the Abbé Principle
Authors: Ren Guoying , Qu Xinghua , Chen Xiangjun
Published: April 2020

Trigger probes are widely used in precision manufacturing industries such as coordinate measuring machines (CMM) and high-end computer numerical control(CNC) machine tools for quality control. Their performance and accuracy often determine the measurement results and the quality of the product manufacturing. However, because there is no accurate measurement of the trigger force in different directions of the probe, and no special measuring device to calibrate the characteristic parameters of the probe in traditional measurement methods, it is impossible to exactly compensate for the measurement error caused by the trigger force of the probe in the measurement process. The accuracy of the measurement of the equipment can be improved by abiding by the Abbé principle. Thus, in order to better evaluate the performance parameters of the probe and realize the accurate compensation for its errors, this paper presents a method which can directly measure the performance parameters of the trigger probe based on the Abbé measurement principle, expounds the measurement principle, the establishment of the mathematical model, and the calibration system, and finishes with an experimental verification and measurement uncertainty analysis. The experimental results show that this method can obtain the exact calibration errors of the performance parameters of the trigger probe intuitively, realize the compensation for the errors of the probe in the measurement process, and effectively improve the measurement accuracy.
Identifying Potential Leakage Zones in an Irrigation Supply Channel by Mapping Soil Properties Using Electromagnetic Induction, Inversion Modelling and a Support Vector Machine
Authors: Zare Ehsan , Li Nan , Khongnawang Tibet , Farzamian Mohammad , Triantafilis John
Published: April 2020

The clay alluvial plains of Namoi Valley have been intensively developed for irrigation. A condition of a license is water needs to be stored on the farm. However, the clay plain was developed from prior stream channels characterised by sandy clay loam textures that are permeable. Cheap methods of soil physical and chemical characterisations are required to map the supply channels used to move water on farms. Herein, we collect apparent electrical conductivity (ECa) from a DUALEM-421 along a 4-km section of a supply channel. We invert ECa to generate electromagnetic conductivity images (EMCI) using EM4Soil software and evaluate two-dimensional models of estimates of true electrical conductivity (σ—mS m−1) against physical (i.e., clay and sand—%) and chemical properties (i.e., electrical conductivity of saturated soil paste extract (ECe—dS m−1) and the cation exchange capacity (CEC, cmol(+) kg−1). Using a support vector machine (SVM), we predict these properties from the σ and depth. Leave-one-site-out cross-validation shows strong 1:1 agreement (Lin’s) between the σ and clay (0.85), sand (0.81), ECe (0.86) and CEC (0.83). Our interpretation of predicted properties suggests the approach can identify leakage areas (i.e., prior stream channels). We suggest that, with this calibration, the approach can be used to predict soil physical and chemical properties beneath supply channels across the rest of the valley. Future research should also explore whether similar calibrations can be developed to enable characterisations in other cotton-growing areas of Australia.
Effects of One Versus Two Doses of a Multi-Ingredient Pre-Workout Supplement on Metabolic Factors and Perceived Exertion during Moderate-Intensity Running in Females
Authors: Erickson Jamie R. , Camic Clayton L. , Jagim Andrew R. , Pellersels Paige M. , Wright Glenn A. , Henert Shaine E. , Foster Carl
Published: April 2020

The primary purpose of this study was to examine the acute effects of one versus two doses of a multi-ingredient pre-workout supplement on energy expenditure during moderate-intensity treadmill running. In addition, our second aim was to investigate the responses of associated metabolic factors (i.e., substrate utilization, measures of gas exchange), perceived exertion, and resting cardiovascular variables with one and two doses of the pre-workout supplement. Twelve females (mean ± SD: age = 25.3 ± 9.4 years; body mass = 61.2 ± 6.8 kg) completed three bouts of 30 min of treadmill running at 90% of their ventilatory threshold on separate days after consuming one dose of the pre-workout supplement (1-dose), two doses (2-dose), and a placebo. There were no differences among conditions for energy expenditure, fat or carbohydrate oxidation, respiratory exchange ratio, oxygen consumption, or heart rate across exercise time. The two-dose group, however, had lower (p = 0.036) ratings of perceived exertion (11.8 ± 1.7) than the one-dose (12.6 ± 1.7) and the placebo (12.3 ± 1.2) at the 20-min time point of exercise as well as greater resting systolic blood pressure (110 ± 10 mmHg) compared to the one-dose (106 ± 10 mmHg) and the placebo (104 ± 10 mmHg) conditions. Both the one-dose and two-dose conditions had greater increases in diastolic blood pressure compared to the placebo. Thus, our findings indicated that the present pre-workout supplement had no performance-enhancing benefits related to energy metabolism but did attenuate feelings of exertion.
Acute Caffeine Supplementation Does Not Improve Performance in Trained CrossFit® Athletes
Authors: Stein Jesse A. , Ramirez Melitza , Heinrich Katie M.
Published: April 2020

Caffeine’s ergogenic effects persist during various exercise modalities; however, information establishing its efficacy during CrossFit® protocols is limited. This study aimed to determine the effects of caffeine supplementation on CrossFit® performance. Twenty CrossFit®-trained men (age = 26.7 ± 6.2 years, experience = 3.7 ± 2.9 years) were randomized in a double-blind, crossover design. Participants completed two sessions separated by a seven-day washout period, 60 min after consuming 5 mg/kg body mass of caffeine or a placebo. In each session, participants completed as many rounds as possible in 20 min of five pull-ups, 10 push-ups, and 15 air squats. CrossFit® performance was the total number of repetitions completed in 20 min. Paired-samples t-tests were used to compare CrossFit® performance between caffeine and placebo conditions and to test for a potential learning effect between the first and second sessions. CrossFit® performance was not significantly different during the caffeine condition compared to the placebo (468.6 ± 114.7 vs. 466.7 ± 94.3 repetitions, p = 0.861). A significant learning effect was identified between the first and second sessions (452.4 ± 101 vs. 483.8 ± 106.5 repetitions, p = 0.001), with no significant effect of treatment order (p = 0.438). Caffeine’s ergogenic effect were not present during the CrossFit® workout “Cindy”; however, future research should include familiarization sessions and examine other CrossFit® workouts in novice and women participants.
Backward Running: Acute Effects on Sprint Performance in Preadolescent Boys
Authors: Petrakis Dimitrios , Bassa Eleni , Papavasileiou Anastasia , Xenofondos Anthi , Patikas Dimitrios A.
Published: April 2020

The aim of this study was to examine the acute effect of backward running (BwR) during warm-up on a 20-m sprint of boys’ performance, compared to forward running (FwR). Fourteen recreationally active preadolescent boys (aged 12.5 ± 0.5 years) were examined in 3 protocols: warm-up (control condition), warm-up with 3 × 10 m additional BwR sprints and warm-up with 3 × 10 m additional FwR sprints. Participants were evaluated 4 minutes after each protocol on a 20-m sprint and intermediate distances, as well as the rate of perceived exertion (RPE). Sprint speed across 10-20 m was significantly higher for the BwR warm-up compared to the regular warm-up (p < 0.05) and a significantly higher RPE after the BwR and FwR protocols compared to the control condition was recorded (p < 0.05). No significant difference was detected across the distances 0–5, 5–10, 0–10 and 0–20 m. Although adding 3 × 10-m sprints of BwR or FwR after the warm-up did not enhance performance in a 20 m sprint of preadolescent boys, the positive effect of BwR across 10–20 m distance suggests that BwR could be an alternative means for enhancing performance for certain phases of a sprint for this age. However, preadolescent boys’ response to different sprint conditioning exercise stimuli and the optimization of rest time to maximize performance remain to be determined.
Systematic Review of Smart Tourism Research
Authors: Ye Ben Haobin , Ye Huiyue , Law Rob
Published: April 2020

In recent decades, smart tourism has been attracting attention from practitioners and scholars. The current study used multiple analysis methods to conduct a systematic review of 124 related articles on smart tourism. Qualitative analysis was conducted to identify 10 categories of smart tourism articles. Results showed that the largest proportion focus on the influence of technology on tourists’ perceptions, behaviors, and experiences. Co-occurrence analysis was performed to investigate the development trend of keywords used by academics in the last five years, while co-authorship (country) analysis was conducted to examine the collaborative relationship between different countries. The research regions, industries, methods, and theories applied in these articles were also analyzed. Theoretical and practical/managerial implications, as well as future research directions, were provided.
Sustainable Cloud Service Provider Development by a Z-Number-Based DNMA Method with Gini-Coefficient-Based Weight Determination
Authors: Lai Han , Liao Huchang , Šaparauskas Jonas , Banaitis Audrius , Ferreira Fernando A. F. , Al-Barakati Abdullah
Published: April 2020

The sustainable development of cloud service providers (CSPs) is a significant multiple criteria decision making (MCDM) problem, involving the intrinsic relations among multiple alternatives, (quantitative and qualitative) decision criteria and decision-experts for the selection of trustworthy CSPs. Most existing MCDM methods for CSP selection incorporated only one normalization technique in benefit and cost criteria, which would mislead the decision results and limit the applications of these methods. In addition, these methods did not consider the reliability of information given by decision-makers. Given these research gaps, this study introduces a Z-number-based double normalization-based multiple aggregation (DNMA) method to tackle quantitative and qualitative criteria in forms of benefit, cost, and target types for sustainable CSP development. We extend the original DNMA method to the Z-number environment to handle the uncertain and unreliability information of decision-makers. To make trade-offs between normalized criteria values, we develop a Gini-coefficient based weighting method to replace the mean-square-based weighting method used in the original DNMA method to enhance the applicability and isotonicity of the DNMA method. A case study is conducted to demonstrate the effectiveness of the proposed method. Furthermore, comparative analysis and sensitivity analysis are implemented to test the stability and applicability of the proposed method.
Collaborative Action for Community Resilience to Climate Risks: Opportunities and Barriers
Authors: Jensen Olivia , Ong Corinne
Published: April 2020

Collaborative actions between citizens and government agencies at the local level have the potential to raise community resilience to climate risks via social learning and increased social capital. However, for these actions to succeed, community members’ values, norms and risk perceptions must support collaborative action and be accompanied by self-efficacy. This paper develops a theoretical framework linking these concepts and applies the framework to a collaborative climate risk project in Singapore, using qualitative data from focus group discussions. We find that pro-social values are a strong enabling factor for residents to engage in collaboration, but that perceptions of low collective efficacy are a potential barrier. In particular, we find that the relative competence of the government leads to a perception of “exemptionalism,” which undermines individuals’ intentions to devote resources to collaborative action.
Effects of Soil and Water Conservation Measures on Runoff and Sediment Yield in Red Soil Slope Farmland under Natural Rainfall
Authors: Chen Xiaoan , Liang Ziwei , Zhang Zhanyu , Zhang Long
Published: April 2020

This paper analyzes the relationship between runoff, soil erosion, sediment particles, and natural rainfall characteristics on sloping farmland in the red soil region of southern China. The surface runoff and soil loss data were measured on runoff plots during 66 natural rainfall events from 2015 to 2018 in Jiangxi Province. The results show that the maximum 30-min rainfall intensity (I30) is positively related to the runoff depth, soil erosion modulus, and sediment mean weight diameter (MWD). With the increase in I30 during rainfall, the coarse sand content increases, and the fine sand content decreases. The average annual runoff of slope tillage, hedgerows with slope tillage, straw mulching with conventional tillage, and contour tillage decreased by 32.56%, 65.87%, 83.99%, and 87.30%, respectively, compared with that of bare land. Soil and water conservation measures can significantly reduce slope runoff. The flow-reduction effect of contour tillage and straw mulching with conventional tillage increases as I30 increases, and the flow-reduction effect of hedgerows with slope tillage first increases and then decreases as I30 increases. The coefficients of variation and standard deviations of the flow-reduction effects of different soil and water conservation measures decrease with increasing I30. The average annual soil erosion moduli of slope tillage, hedgerows with slope tillage, contour tillage, and straw mulching with conventional tillage decreased by 59.33%, 91.29%, 97.17%, and 98.45%, respectively, compared with that of bare land. Soil and water conservation measures can significantly reduce the sediment yield on slopes. The flow-reduction effects of hedgerows with slope tillage, contour tillage, and straw mulching with conventional tillage all increase with I30, and their coefficients of variation and standard deviations decrease with I30. The average single rainfall erosion sediment MWD of decreased by 5.91%, 8.33%, 9.69%, and 13.32%, respectively, compared with that of bare land. Straw mulching with conventional tillage can significantly reduce the MWD of erosion sediment, effectively reduce the content of coarse sand, and increase the content of fine sand. Straw mulching with conventional tillage is a very good soil and water conservation measure for sloping farmland. It not only has the best effect on reducing flow and sediment, but also can effectively intercept coarse sand and reduce the MWD of erosion sediment.
Topic Modeling Analysis of Social Enterprises: Twitter Evidence
Authors: Kao Shr-Wei , Luarn Pin
Published: April 2020

Social media is a major channel used for communication by professional and social groups. The text posted on social media contains extremely rich information. To capture the development of social enterprises (SEs), this paper examines the tweets posted on Twitter and searches the hashtags on the Twitter Application Programming Interface (API) that SEs deem to be the most important. The results suggest that these tweets can be divided into three content groups (strategy, impact and business). This paper expands this into four dimensions (strategy, impact, business and people) and six indicators (social, opportunity, change, enterprise, network and team) and establishes a conceptual framework of SEs. This paper aims to enhance the understanding of the pertinent issues recently affecting SEs and extract findings that can act as a reference for follow-up studies.
ICT Implementation and Its Effect on Public Organizations: The Case of Digital Customs and Risk Management in Korea
Authors: Kim Sung-Bou , Kim Dongwook
Published: April 2020

Technological advancement and globalization have led modern economic growth and social development in many parts of the world. Governments are also increasingly adopting new technology to uphold public safety and to protect its citizens. In particular, customs administrations have been adopting digital customs and risk management frameworks to promote free trade and traveling while preventing cross-border transport of dangerous goods and individuals. This study proposes an up-to-date dynamic information and communications technology (ICT) implementation stage model that accounts for new modern technology and transformative public organizations. An in-depth case study approach is employed by using the example of the customs services in South Korea. Specifically, this study describes how the Korea Customs Service developed its digital customs system in tandem with risk management guidelines and practices and presents quantitative data on customs and risk management outcomes.
Effect of Potato Tuber Exposure to UV-C Radiation and Semi-Product Soaking in Water on Acrylamide Content in French Fries Dry Matter
Authors: Sobol Zygmunt , Jakubowski Tomasz , Surma Magdalena
Published: April 2020

This study aims to determine the effect of raw potato tubers’ exposure to UV-C radiation and semi-products soaking in water on the content of acrylamide in the dry matter of French fries. The French fries were prepared from tubers of the Innovator variety of potato (Solanum tuberosum L.). Acrylamide contents were determined by HPLC-UV/Vis on a C-18 column after extraction of fried potatoes with acetonitrile. Potato tubers exposure to UV-C radiation caused an increase in acrylamide content and the soaking of semi-products in water caused a decrease in acrylamide content in the dry matter of French fries.
The Effect of Averaging, Sampling, and Time Series Length on Wind Power Density Estimations
Authors: Gross Markus , Magar Vanesa , Peña Alfredo
Published: April 2020

The Wind Power Density (WPD) is widely used for wind resource characterization. However, there is a significant level of uncertainty associated with its estimation. Here, we analyze the effect of sampling frequencies, averaging periods, and the length of time series on the WPD estimation. We perform this analysis using four approaches. First, we analytically evaluate the impact of assuming that the WPD can simply be computed from the cube of the mean wind speed. Second, the wind speed time series from two meteorological stations are used to assess the effect of sampling and averaging on the WPD. Third, we use numerical weather prediction model outputs and observational data to demonstrate that the error in the WPD estimate is also dependent on the length of the time series. Finally, artificial time series are generated to control the characteristics of the wind speed distribution, and we analyze the sensitivity of the WPD to variations of these characteristics. The WPD estimation error is expressed mathematically using a numerical-data-driven model. This numerical-data-driven model can then be used to predict the WPD estimation errors at other sites. We demonstrate that substantial errors can be introduced by choosing too short time series. Furthermore, averaging leads to an underestimation of the WPD. The error introduced by sampling is strongly site-dependent.
Quantifying the Effects of Biochar Application on Greenhouse Gas Emissions from Agricultural Soils: A Global Meta-Analysis
Authors: Zhang Qi , Xiao Jing , Xue Jianhui , Zhang Lang
Published: April 2020

Agricultural disturbance has significantly boosted soil greenhouse gas (GHG) emissions such as methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O). Biochar application is a potential option for regulating soil GHG emissions. However, the effects of biochar application on soil GHG emissions are variable among different environmental conditions. In this study, a dataset based on 129 published papers was used to quantify the effect sizes of biochar application on soil GHG emissions. Overall, biochar application significantly increased soil CH4 and CO2 emissions by an average of 15% and 16% but decreased soil N2O emissions by an average of 38%. The response ratio of biochar applications on soil GHG emissions was significantly different under various management strategies, biochar characteristics, and soil properties. The relative influence of biochar characteristics differed among soil GHG emissions, with the overall contribution of biochar characteristics to soil GHG emissions ranging from 29% (N2O) to 71% (CO2). Soil pH, the biochar C:N ratio, and the biochar application rate were the most influential variables on soil CH4, CO2, and N2O emissions, respectively. With biochar application, global warming potential (impact of the emission of different greenhouse gases on their radiative forcing by agricultural practices) and the intensity of greenhouse gas emissions (emission rate of a given pollutant relative to the intensity of a specific activity) significantly decreased, and crop yield greatly increased, with an average response ratio of 23%, 41%, and 21%, respectively. Our findings provide a scientific basis for reducing soil GHG emissions and increasing crop yield through biochar application.
Changes in Climatic Water Availability and Crop Water Demand for Iraq Region
Authors: Salman Saleem A. , Shahid Shamsuddin , Afan Haitham Abdulmohsin , Shiru Mohammed Sanusi , Al-Ansari Nadhir , Yaseen Zaher Mundher
Published: April 2020

Decreases in climatic water availability (CWA) and increases in crop water demand (CWD) in the background of climate change are a major concern in arid regions because of less water availability and higher irrigation requirements for crop production. Assessment of the spatiotemporal changes in CWA and CWD is important for the adaptation of irrigated agriculture to climate change for such regions. The recent changes in CWA and CWD during growing seasons of major crops have been assessed for Iraq where rapid changes in climate have been noticed in recent decades. Gridded precipitation of the global precipitation climatology center (GPCC) and gridded temperature of the climate research unit (CRU) having a spatial resolution of 0.5°, were used for the estimation of CWA and CWD using simple water balance equations. The Mann–Kendall (MK) test and one of its modified versions which can consider long-term persistence in time series, were used to estimate trends in CWA for the period 1961–2013. In addition, the changes in CWD between early (1961–1990) and late (1984–2013) periods were evaluated using the Wilcoxon rank test. The results revealed a deficit in water in all the seasons in most of the country while a surplus in the northern highlands in all the seasons except summer was observed. A significant reduction in the annual amount of CWA at a rate of −1 to −13 mm/year was observed at 0.5 level of significance in most of Iraq except in the north. Decreasing trends in CWA in spring (−0.4 to −1.8 mm/year), summer (−5.0 to −11 mm/year) and autumn (0.3 to −0.6 mm/year), and almost no change in winter was observed. The CWA during the growing season of summer crop (millet and sorghum) was found to decrease significantly in most of Iraq except in the north. The comparison of CWD revealed an increase in agricultural water needs in the late period (1984–2013) compared to the early period (1961–1990) by 1.0–8.0, 1.0–14, 15–30, 14–27 and 0.0–10 mm for wheat, barley, millet, sorghum and potato, respectively. The highest increase in CWD was found in April, October, June, June and April for wheat, barley, millet, sorghum and potato, respectively.