bluuebunny/crossref_metadata_2025 huggingface dataset:
‘Prescription’ for Purposeful Adaptation of Professionalism-and-Ethics Teaching Strategies for Remote Delivery
Authors: Roche Cicely
Published: March 2021

This case report outlines the strategies underpinning the adaptation of professionalism and ethics strand (P&E) teaching for remote delivery on a Pharmacy programme in response to COVID-19 restrictions. In line with national and University guidance, P&E teaching detailed in this report was delivered online in late 2020. Sessions were generally live and recorded, although some content was pre-recorded using video-capture software. All learning activities, recordings and supporting resources are accessible to students on the University’s Virtual Learning Environment. This report reflects on the curriculum, pedagogy and content of P&E teaching, with particular emphasis on teaching related to professional identity formation and moral reasoning competencies development. Design, development and delivery of remote online teaching is considered in the context of P&E teaching. Strategies used to plan for adaptation and delivery of interactive online teaching sessions aligned with P&E teaching are described. Key findings support a scholarship of teaching approach when planning for adaptation to remote online teaching. Purposeful consideration of existing curricular, pedagogical and instructional design enables the teacher to identify critical P&E teaching activities potentially compromised by the move to the online environment. Informed integration of available instructional tools to teaching activities follows. The report concludes with recommendations for future research.
Near- to Far-Field Coupling of Evanescent Waves by Glass Microspheres
Authors: Boudoukha Rayenne , Perrin Stephane , Demagh Assia , Montgomery Paul , Demagh Nacer-Eddine , Lecler Sylvain
Published: March 2021

Through rigorous electromagnetic simulations, the natural coupling of high-spatial-frequency evanescent waves from the near field to the far field by dielectric microspheres is studied in air. The generation of whispering gallery modes inside the microspheres is shown independently of any resonance. In addition, the conversion mechanism of these evanescent waves into propagating waves is analysed. This latter point leads to key information that allows a better physical understanding of the super-resolution phenomenon in microsphere-assisted microscopy where sub-diffraction-limit revolving power is achieved.
Cubing Fabrication/Costing and Machine Performance on African Fermented Condiment Quality Attributes Compared with Commercial Bouillon Types
Authors: Uzodinma Eunice O. , Okoyeuzu Chigozie F. , Uchegbu Nneka N. , Okpala Charles Odilichukwu R. , Rasaq Waheed A. , Shorstkii Ivan , Sardo Giacomo , Bono Gioacchino , Korzeniowska Małgorzata
Published: March 2021

Cubing machines in food processing have evolved over the years, which have made products like Star®, Knorr®, and Chicken® bouillon cubes become commercially available today, even in many parts of Africa. On the other hand, the fermented mesquite seed “okpeye” food condiment, traditionally produced by well-trained artisans and widely utilised in Nigeria, requires further product development in order to compete with bouillon cubes. Quality comparisons between the cubed “okpeye” condiment and commercially available bouillon cube products have not yet been reported. Therefore, cubing fabrication/costing and machine performance on African fermented “okpeye” condiment quality attributes, compared with commercial bouillon types, were done. The processing of mesquite seeds into the “okpeye” condiment resembled those of artisans. Bouillon cube products involved the Star®, Knorr®, and Chicken® types. Quality attributes involved proximate, micronutrient, phytochemical, and microbial aspects. Results showed that the throughput capacity of a cubing machine increased with an efficiency of 48 condiment cubes/min, forming properly without separation. Across all studied samples, the protein, ash, moisture, crude fat, crude fibre, and carbohydrate contents were in the range of 1.45–42.50%, 5.29–6.75%, 8.50–12.29%, 2.56–18.54%, 2.45–3.19%, and 18.16–25.56%, respectively. The protein, fat, moisture, calcium, iron, magnesium, and manganese contents of “okpeye” condiment were significantly higher (p < 0.05) than those of bouillon cubes. Fair amounts of vitamins B1, B2, B3, and E were found, with the “okpeye” condiment higher in vitamin E. Besides the flavonoids (0.12–0.18%), alkaloids (0.08–0.15%), saponins (0.19–0.55%), and tannins (0.69–0.93%) present, the microbial loads were similar (p > 0.05) across all samples. Indeed, the “okpeye” condiment can be cubed, and by quality attribute, it competes favourably, and very promising substitute to commercial bouillon cubes.
Mechanical Response and Deformation Mechanisms of TB17 Titanium Alloy at High Strain Rates
Authors: Chen Xinchi , Zhang Xiaoyong , Chen Chao , Zhou Kechao
Published: March 2021

The mechanical response and deformation mechanisms of TB17 titanium alloy were studied at room temperature by the split-Hopkinson pressure bar test. The ultimate compression strength increases from 1050 MPa to 1400 MPa, as the strain rate increases from 2000 s−1 to 2800 s−1. The adiabatic shear failure occurred at strain rate 2800 s−1. When the strain rate was 2000 s−1, only {10 9 3}<331>β type II high index deformation twins, a small number of α” martensite, and interfacial ω phase were detected. When the strain rate was 2400 s−1 and above, multiple deformation mechanisms, including the primary {10 9 3}<331>β type II high index deformation twins, secondary {332}<113>β deformation twins, and α” martensite were identified. The deformation mechanism changes from primary deformation twins and α” martensite to multiple deformation mechanisms (primary and secondary deformation structure) with the increase of strain rates.
An Image Stitching Method for Airborne Wide-Swath HyperSpectral Imaging System Equipped with Multiple Imagers
Authors: Li Jingmei , Ma Lingling , Fan Yongxiang , Wang Ning , Duan Keke , Han Qijin , Zhang Xuyuan , Su Guozhong , Li Chuanrong , Tang Lingli
Published: March 2021

The field of view (FOV) of pushbroom hyperspectral imager is limited by the compromise of the detector scale and requirements of spatial resolution. Combining imagers along the sampling direction effectively expands its FOV and improves the imaging efficiency. Due to the small overlapping area between the adjacent imagers, stitching the images using traditional methods need a large amount of ground control points (GCPs) or additional strips, which reduce the efficiency of both image acquisition and processing. This paper proposed a new method to precisely stitch images acquired from multiple pushbroom imagers. First, the relative orientation model was built based on the homonymy points to calculate the relative relationship between the adjacent imagers. Then rigorous geometric imaging model was adopted to generate a seamless stitching image. Simulation data was used to verify the accuracy of the method and to quantitatively analyze the effect of different error sources. Results show that the stitching accuracy is better than two pixels. Overall, this method provides a novel solution for stitching airborne multiple pushbroom images, to generate the seamless stitching image with wide FOV.
Shipborne Mobile Photogrammetry for 3D Mapping and Landslide Detection of the Water-Level Fluctuation Zone in the Three Gorges Reservoir Area, China
Authors: Jin Dingjian , Li Jing , Gong Jianhua , Li Yi , Zhao Zheng , Li Yongzhi , Li Dan , Yu Kun , Wang Shanshan
Published: March 2021

The water-level fluctuation zone (WLFZ) of the Three Gorges Reservoir is a serious landslide-prone area. However, current remote sensing methods for landslide mapping and detection in the WLFZ are insufficient because of difficulties in data acquisition and lack of facade information. We proposed a novel shipborne mobile photogrammetry approach for 3D mapping and landslide detection in the WLFZ for the first time, containing a self-designed shipborne hardware platform and a data acquisition and processing workflow. To evaluate the accuracy and usability of the resultant 3D models in the WLFZ, four bundle block adjustment (BBA) control configurations were developed and adopted. In the four configurations, the raw Global Navigation Satellite System (GNSS) data, the raw GNSS data and fixed camera height, the GCPs extracted from aerial photogrammetric products, and the mobile Light Detection and Ranging (LiDAR) point cloud were used. A comprehensive accuracy assessment of the 3D models was conducted, and the comparative results indicated the BBA with GCPs extracted from the aerial photogrammetric products was the most practical configuration (RMSE 2.00 m in plane, RMSE 0.46 m in height), while the BBA with the mobile LiDAR point cloud as a control provided the highest georeferencing accuracy (RMSE 0.59 m in plane, RMSE 0.40 m in height). Subsequently, the landslide detection ability of the proposed approach was compared with multisource remote sensing images through visual interpretation, which showed that the proposed approach provided the highest landslide detection rate and unique advantages in small landslide detection as well as in steep terrains due to the more detailed features of landslides provided by the shipborne 3D models. The approach is an effective and flexible supplement to traditional remote sensing methods.
Review of Road Segmentation for SAR Images
Authors: Sun Zengguo , Geng Hui , Lu Zheng , Scherer Rafał , Woźniak Marcin
Published: March 2021

Road segmentation for synthetic aperture radar (SAR) images is of great practical significance. With the rapid development and wide application of SAR imaging technology, this problem has attracted much attention. At present, there are numerous road segmentation methods. This paper analyzes and summarizes the road segmentation methods for SAR images over the years. Firstly, the traditional road segmentation algorithms are classified according to the degree of automation and the principle. Advantages and disadvantages are introduced successively for each traditional method. Then, the popular segmentation methods based on deep learning in recent years are systematically introduced. Finally, novel deep segmentation neural networks based on the capsule paradigm and the self-attention mechanism are forecasted as future research for SAR images.
Determination of Process Noise for Underwater Target Tracking with Forward Looking Sonar
Authors: Kazimierski Witold , Zaniewicz Grzegorz
Published: March 2021

Target tracking is a process that provides information about targets in a specific area and is one of the key issues affecting the safety of any vehicle navigating in water. The main sensor used for underwater target tracking is sonar, with one of the most popular configurations being forward looking sonar (FLS). The target tracking state vector is usually estimated with the use of numerical filter algorithms, such as the Kalman filter (KF) and its modification, or the particle filter (PF). This requires the definition of a process model, including process noise, and a measurement model. This study focused on process noise definition. It is usually implemented as Gaussian noise, with a covariance matrix defined by the author. An analytical and empirical analysis was conducted, including a verification of the existing approaches and a survey of the published literature. Additionally, a theoretical analysis of the factors influencing process noise was conducted, which was followed by an empirical verification. The results were discussed, leading to the conclusions. The results of the theoretical analysis were confirmed by the empirical experiment and the results were compared with commonly used values of process noise in underwater target tracking processes.
A Novel GFDM Waveform Design Based on Cascaded WHT-LWT Transform for the Beyond 5G Wireless Communications
Authors: Maraş Meryem , Ayvaz Elif Nur , Gömeç Meltem , Savaşcıhabeş Asuman , Özen Ali
Published: March 2021

In this paper, a new WHT-LWT-GFDM waveform obtained by combining Walsh–Hadamard Transform (WHT), Lifting Wavelet Transform (LWT), and Generalized Frequency Division Multiplexing (GFDM) is presented for use in next-generation wireless communication systems. The proposed approach meets the requirement of 5th-generation (5G) and beyond communication schemes in terms of low latency, low peak-to-average-power ratio (PAPR), and low bit-error rate (BER). To verify the performance of the presented waveform, PAPR and BER simulation results were obtained in additive white Gaussian noise (AWGN) and flat Rayleigh fading channels, and the performance of the proposed system was compared with conventional Orthogonal Frequency Division Multiplexing (OFDM), GFDM, and Walsh–Hadamard transform-based GFDM (WHT-GFDM). Simulation results show that the proposed waveform achieves the best BER and PAPR performances and it provides considerable performance gains over the conventional waveforms.
Body and Hand–Object ROI-Based Behavior Recognition Using Deep Learning
Authors: Byeon Yeong-Hyeon , Kim Dohyung , Lee Jaeyeon , Kwak Keun-Chang
Published: March 2021

Behavior recognition has applications in automatic crime monitoring, automatic sports video analysis, and context awareness of so-called silver robots. In this study, we employ deep learning to recognize behavior based on body and hand–object interaction regions of interest (ROIs). We propose an ROI-based four-stream ensemble convolutional neural network (CNN). Behavior recognition data are mainly composed of images and skeletons. The first stream uses a pre-trained 2D-CNN by converting the 3D skeleton sequence into pose evolution images (PEIs). The second stream inputs the RGB video into the 3D-CNN to extract temporal and spatial features. The most important information in behavior recognition is identification of the person performing the action. Therefore, if the neural network is trained by removing ambient noise and placing the ROI on the person, feature analysis can be performed by focusing on the behavior itself rather than learning the entire region. Therefore, the third stream inputs the RGB video limited to the body-ROI into the 3D-CNN. The fourth stream inputs the RGB video limited to ROIs of hand–object interactions into the 3D-CNN. Finally, because better performance is expected by combining the information of the models trained with attention to these ROIs, better recognition will be possible through late fusion of the four stream scores. The Electronics and Telecommunications Research Institute (ETRI)-Activity3D dataset was used for the experiments. This dataset contains color images, images of skeletons, and depth images of 55 daily behaviors of 50 elderly and 50 young individuals. The experimental results showed that the proposed model improved recognition by at least 4.27% and up to 20.97% compared to other behavior recognition methods.
Design and Implementation of Universal Cyber-Physical Model for Testing Logistic Control Algorithms of Production Line’s Digital Twin by Using Color Sensor
Authors: Vachálek Ján , Šišmišová Dana , Vašek Pavol , Fiťka Ivan , Slovák Juraj , Šimovec Matej
Published: March 2021

This paper deals with the design and implementation of a universal cyber-physical model capable of simulating any production process in order to optimize its logistics systems. The basic idea is the direct possibility of testing and debugging advanced logistics algorithms using a digital twin outside the production line. Since the digital twin requires a physical connection to a real line for its operation, this connection is substituted by a modular cyber-physical system (CPS), which replicates the same physical inputs and outputs as a real production line. Especially in fully functional production facilities, there is a trend towards optimizing logistics systems in order to increase efficiency and reduce idle time. Virtualization techniques in the form of a digital twin are standardly used for this purpose. The possibility of an initial test of the physical implementation of proposed optimization changes before they are fully implemented into operation is a pragmatic question that still resonates on the production side. Such concerns are justified because the proposed changes in the optimization of production logistics based on simulations from a digital twin tend to be initially costly and affect the existing functional production infrastructure. Therefore, we created a universal CPS based on requirements from our cooperating manufacturing companies. The model fully physically reproduces the real conditions of simulated production and verifies in advance the quality of proposed optimization changes virtually by the digital twin. Optimization costs are also significantly reduced, as it is not necessary to verify the optimization impact directly in production, but only in the physical model. To demonstrate the versatility of deployment, we chose a configuration simulating a robotic assembly workplace and its logistics.
A Graphene-Based Enzymatic Biosensor Using a Common-Gate Field-Effect Transistor for L-Lactic Acid Detection in Blood Plasma Samples
Authors: Schuck Ariadna , Kim Hyo Eun , Moreira Júlia Konzen , Lora Priscila Schmidt , Kim Yong-Sang
Published: March 2021

Lactate is an important organic molecule that is produced in excess during anaerobic metabolism when oxygen is absent in the human organism. The concentration of this substance in the body can be related to several medical conditions, such as hemorrhage, respiratory failure, and ischemia. Herein, we describe a graphene-based lactate biosensor to detect the concentrations of L-lactic acid in different fluids (buffer solution and plasma). The active surface (graphene) of the device was functionalized with lactate dehydrogenase enzyme using different substances (Nafion, chitosan, and glutaraldehyde) to guarantee stability and increase selectivity. The devices presented linear responses for the concentration ranges tested in the different fluids. An interference study was performed using ascorbic acid, uric acid, and glucose, and there was a minimum variation in the Dirac point voltage during detection of lactate in any of the samples. The stability of the devices was verified at up to 50 days while kept in a dry box at room temperature, and device operation was stable until 12 days. This study demonstrated graphene performance to monitor L-lactic acid production in human samples, indicating that this material can be implemented in more simple and low-cost devices, such as flexible sensors, for point-of-care applications.
Comparing Kriging Estimators Using Weather Station Data and Local Greenhouse Sensors
Authors: Kuo Pei-Fen , Huang Tzu-En , Putra I Gede Brawiswa
Published: March 2021

In order to minimize the impacts of climate change on various crops, farmers must learn to monitor environmental conditions accurately and effectively, especially for plants that are particularly sensitive to the weather. On-site sensors and weather stations are two common methods for collecting data and observing weather conditions. Although sensors are capable of collecting accurate weather information on-site, they can be costly and time-consuming to install and maintain. An alternative is to use the online weather stations, which are usually government-owned and free to the public; however, their accuracy is questionable because they are frequently located far from the farmers’ greenhouses. Therefore, we compared the accuracy of kriging estimators using the weather station data (collected by the Central Weather Bureau) to local sensors located in the greenhouse. The spatio-temporal kriging method was used to interpolate temperature data. The real value at the central point of the greenhouse was used for comparison. According to our results, the accuracy of the weather station estimator was slightly lower than that of the local sensor estimator. Farmers can obtain accurate estimators of environmental data by using on-site sensors; however, if they are unavailable, using a nearby weather station estimator is also acceptable.
Validation of Walking Speed Estimation from Trunk Mounted Accelerometers for a Range of Walking Speeds
Authors: Rispens Sietse M. , Cox Lieke G. E. , Ejupi Andreas , Delbaere Kim , Annegarn Janneke , Bonomi Alberto G.
Published: March 2021

Walking speed is a strong indicator of the health status of older people and patients. Using algorithms, the walking speed can be estimated from wearable accelerometers, which enables minimally obtrusive (longitudinal) monitoring. We evaluated the performance of two algorithms, the inverted pendulum (IP) algorithm, and a novel adaptation correcting for lateral step movement, which aimed to improve accuracy during slow walking. To evaluate robustness, we gathered data from different groups (healthy adults, elderly, and elderly patients) of volunteers (n = 159) walking under various conditions (over ground, treadmill, using walking aids) at a broad range of speeds (0.11–1.93 m/s). Both of the algorithms showed good agreement with the reference values and similar root-mean-square errors (RMSEs) for walking speeds ≥0.5 m/s, which ranged from 0.09–0.16 m/s for the different positions, in line with the results from others. However, for slower walking, RMSEs were significantly better for the new method (0.06–0.09 m/s versus 0.15–0.19 m/s). Pearson correlation improved for speeds <0.5 m/s (from 0.67–0.72 to 0.73–0.82) as well as higher speeds (0.87–0.97 to 0.90–0.98) with the new method. Overall, we found that IP(-based) walking speed estimation proved to be applicable for a variety of wearing positions, conditions and speeds, indicating its potential value for health assessment applications.
Radiometric Performance Evaluation of FY-4A/AGRI Based on Aqua/MODIS
Authors: Zhong Bo , Ma Yingbo , Yang Aixia , Wu Junjun
Published: March 2021

Fengyun-4A (FY-4A) is the first satellite of the Chinese second-generation geostationary orbit meteorological satellites (FY-4). The Advanced Geostationary Radiation Imager (AGRI), onboard FY-4A does not load with high-precision calibration facility in visible and near infrared (VNIR) channel. As a consequence, it is necessary to comprehensively evaluate its radiometric performance and quantitatively describe the attenuation while using its VNIR data. In this paper, the radiometric performance at VNIR channels of FY-4A/AGRI is evaluated based on Aqua/MODIS data using the deep convective cloud (DCC) target. In order to reduce the influence of view angle and spectral response difference, the bi-directional reflectance distribution function (BRDF) correction and spectral matching have been performed. The evaluation result shows the radiometric performance of FY-4A/AGRI: (1) is less stable and with obvious fluctuations; (2) has a lower radiation level because of 24.99% lower compared with Aqua/MODIS; 3) has a high attenuation with 9.11% total attenuation over 2 years and 4.0% average annual attenuation rate. After the evaluation, relative radiometric normalization between AGRI and MODIS in VNIR channel is performed and the procedure is proved effective. This paper proposed a more reliable reference for the quantitative applications of FY-4A data.
From Smartphone Lateral Flow Immunoassay Screening to Direct MS Analysis: Development and Validation of a Semi-Quantitative Direct Analysis in Real-Time Mass Spectrometric (DART-MS) Approach to the Analysis of Deoxynivalenol
Authors: Geballa-Koukoula Ariadni , Gerssen Arjen , Nielen Michel W. F.
Published: March 2021

In current food safety monitoring, lateral flow immunoassays (LFIAs) are widely used for rapid food contaminant screening. Recent advances include smartphone readouts, offering semi-quantitative analysis of LFIAs with time, location, and data transfer in case of on-site testing. Following the screening, the next step in the EU regulations is confirmation by, e.g., liquid chromatography-tandem mass spectrometry (LC-MS/MS). In this work, using direct analysis in real time ambient ionization and triple quadrupole MS/MS (DART-QqQ-MS/MS), we achieved rapid confirmation of the identity of the substance(s) causing the LFIA result. In the workflow proposed, an individual performs the (on-site) smartphone LFIA screening, and when the result is suspect, an identification LFIA (ID-LFIA) strip is developed with the same sample extract. The ID-LFIA can be dissociated and rapidly analyzed in a control laboratory with DART-QqQ-MS/MS. The ID-LFIA consists of multiple lines of monoclonal antibodies against the mycotoxin deoxynivalenol, acting as a bioaffinity trap. The ID-LFIA/DART-QqQ-MS/MS approach has been developed and validated, along with the screening smartphone LFIA, and has demonstrated its applicability by analyzing incurred and spiked samples. The developed approach has been critically compared with our previous direct electrospray ionization MS method and was found to provide highly complementary information on the total deoxynivalenol contamination in the sample.
An Estimation Method of Continuous Non-Invasive Arterial Blood Pressure Waveform Using Photoplethysmography: A U-Net Architecture-Based Approach
Authors: Athaya Tasbiraha , Choi Sunwoong
Published: March 2021

Blood pressure (BP) monitoring has significant importance in the treatment of hypertension and different cardiovascular health diseases. As photoplethysmogram (PPG) signals can be recorded non-invasively, research has been highly conducted to measure BP using PPG recently. In this paper, we propose a U-net deep learning architecture that uses fingertip PPG signal as input to estimate arterial BP (ABP) waveform non-invasively. From this waveform, we have also measured systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP). The proposed method was evaluated on a subset of 100 subjects from two publicly available databases: MIMIC and MIMIC-III. The predicted ABP waveforms correlated highly with the reference waveforms and we have obtained an average Pearson’s correlation coefficient of 0.993. The mean absolute error is 3.68 ± 4.42 mmHg for SBP, 1.97 ± 2.92 mmHg for DBP, and 2.17 ± 3.06 mmHg for MAP which satisfy the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) standard and obtain grade A according to the British Hypertension Society (BHS) standard. The results show that the proposed method is an efficient process to estimate ABP waveform directly using fingertip PPG.
Direct Scaling of Measure on Vortex Shedding through a Flapping Flag Device in the Open Channel around a Cylinder at Re∼103: Taylor’s Law Approach
Authors: De Bartolo Samuele , Vittorio Massimo De , Francone Antonio , Guido Francesco , Leone Elisa , Mastronardi Vincenzo Mariano , Notaro Andrea , Tomasicchio Giuseppe Roberto
Published: March 2021

The problem of vortex shedding, which occurs when an obstacle is placed in a regular flow, is governed by Reynolds and Strouhal numbers, known by dimensional analysis. The present work aims to propose a thin films-based device, consisting of an elastic piezoelectric flapping flag clamped at one end, in order to determine the frequency of vortex shedding downstream an obstacle for a flow field at Reynolds number Re∼103 in the open channel. For these values, Strouhal number obtained in such way is in accordance with the results known in literature. Moreover, the development of the voltage over time, generated by the flapping flag under the load due to flow field, shows a highly fluctuating behavior and satisfies Taylor’s law, observed in several complex systems. This provided useful information about the flow field through the constitutive law of the device.
Forecasting Key Retail Performance Indicators Using Interpretable Regression
Authors: Panay Belisario , Baloian Nelson , Pino José A. , Peñafiel Sergio , Frez Jonathan , Fuenzalida Cristóbal , Sanson Horacio , Zurita Gustavo
Published: March 2021

Foot traffic, conversion rate, and total sales during a period of time may be considered to be important indicators of store performance. Forecasting them may allow for business managers plan stores operation in the near future in an efficient way. This work presents a regression method that is able to predict these three indicators based on previous data. The previous data includes values for the indicators in the recent past; therefore, it is a requirement to have gathered them in a suitable manner. The previous data also considers other values that are easily obtained, such as the day of the week and hour of the day of the indicators. The novelty of the approach that is presented here is that it provides a confidence interval for the predicted information and the importance of each parameter for the predicted output values, without additional processing or analysis. Real data gathered by Follow Up, a customer experience company, was used to test the proposed method. The method was tried for making predictions for up to one month in the future. The results of the experiments show that the proposed method has a comparable performance to the best methods proposed in the past that do not provide confidence intervals or parameter rankings. The method obtains RMSE of 0.0713 for foot traffic prediction, 0.0795 for conversion rate forecasting, and 0.0757 for sales prediction.
RF-Based Moisture Content Determination in Rice Using Machine Learning Techniques
Authors: Azmi Noraini , Kamarudin Latifah Munirah , Zakaria Ammar , Ndzi David Lorater , Rahiman Mohd Hafiz Fazalul , Zakaria Syed Muhammad Mamduh Syed , Mohamed Latifah
Published: March 2021

Seasonal crops require reliable storage conditions to protect the yield once harvested. For long term storage, controlling the moisture content level in grains is challenging because existing moisture measuring techniques are time-consuming and laborious as measurements are carried out manually. The measurements are carried out using a sample and moisture may be unevenly distributed inside the silo/bin. Numerous studies have been conducted to measure the moisture content in grains utilising dielectric properties. To the best of authors’ knowledge, the utilisation of low-cost wireless technology operating in the 2.4 GHz and 915 MHz ISM bands such as Wireless Sensor Network (WSN) and Radio Frequency Identification (RFID) have not been widely investigated. This study focuses on the characterisation of 2.4 GHz Radio Frequency (RF) transceivers using ZigBee Standard and 868 to 915 MHz UHF RFID transceiver for moisture content classification and prediction using Artificial Neural Network (ANN) models. The Received Signal Strength Indicator (RSSI) from the wireless transceivers is used for moisture content prediction in rice. Four samples (2 kg of rice each) were conditioned to 10%, 15%, 20%, and 25% moisture contents. The RSSI from both systems were obtained and processed. The processed data is used as input to different ANNs models such as Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Random Forest, and Multi-layer Perceptron (MLP). The results show that the Random Forest method with one input feature (RSSI_WSN) provides the highest accuracy of 87% compared to the other four models. All models show more than 98% accuracy when two input features (RSSI_WSN and RSSI_TAG2) are used. Hence, Random Forest is a reliable model that can be used to predict the moisture content level in rice as it gives a high accuracy even when only one input feature is used.
Comparison of Dual Beam Dispersive and FTNIR Spectroscopy for Lactate Detection
Authors: Baishya Nystha , Mamouei Mohammad , Budidha Karthik , Qassem Meha , Vadgama Pankaj , Kyriacou Panayiotis A.
Published: March 2021

Near Infrared (800–2500 nm) spectroscopy has been extensively used in biomedical applications, as it offers rapid, in vivo, bed-side monitoring of important haemodynamic parameters, which is especially important in critical care settings. However, the choice of NIR spectrometer needs to be investigated for biomedical applications, as both the dual beam dispersive spectrophotomer and the FTNIR spectrometer have their own advantages and disadvantages. In this study, predictive analysis of lactate concentrations in whole blood were undertaken using multivariate techniques on spectra obtained from the two spectrometer types simultaneously and results were compared. Results showed significant improvement in predicting analyte concentration when analysis was performed on full range spectral data. This is in comparison to analysis of limited spectral regions or lactate signature peaks, which yielded poorer prediction models. Furthermore, for the same region, FTNIR showed 10% better predictive capability than the dual beam dispersive NIR spectrometer.
Amidst Covid-19 Pandemic: An Adaptive Disaster Governance in Yogyakarta, Indonesia
Authors: Hizbaron Dyah Rahmawati , Ruslanjari Dina , Mardiatno Djati
Published: March 2021

Since Indonesia reported its first case of COVID-19 in the capital, Jakarta, in early March of 2020, the pandemic has affected 102,051,000 lives. In the second week of the month, the government mandated all sectors to take necessary actions to curb the spread. The research set out to evaluate how the disaster emergency response was carried out amid the COVID-19 pandemic in the Special Region of Yogyakarta (SRY). The research employs qualitative observation of adaptive governance variables, i.e., infrastructure availability, information, conflict mechanism, regulation, and adaptation. The research analyzed primary data collected from focus group discussions with key persons at the Local Disaster Management Agency, Local Development Planning Agency, and Disaster Risk Reduction Platform responsible for the crisis and included an online survey to validate data. The research revealed that the SRY had exhibited adaptive governance to the COVID-19 pandemic, as apparent by, among others, open-access spatial and non-spatial data, extensive combined uses of both types of data, and prompt active engagement of communities in the enforcement of new rules and regulations mandated by national and provincial governments. Furthermore, during emergency responses to COVID-19, the stakeholders provided infrastructure and information, dealt with conflicts in multiple spatial units, encouraged adaptations, and formulated emergent rules and regulations. For further research, we encourage qualitative analysis to confront other types of natural disaster for the research area.
Genome-Wide Analysis of the Trihelix Gene Family and Their Response to Cold Stress in Dendrobium officinale
Authors: Tong Yan , Huang Hui , Wang YuHua
Published: March 2021

Trihelix transcription factors play important roles in plant growth, development and various stress responses. In this study, we identified 32 trihelix family genes (DoGT) in the important Chinese medicinal plant Dendrobium officinale. These trihelix genes could be classified into five different subgroups. The gene structure and conserved functional domain of these trihelix genes were similar in the same subfamily but diverged between different subfamilies. Various stresses responsive cis-elements presented in the promoters of DoGT genes, suggesting that the trihelix genes might respond to the environmental stresses. Expressional changes of DoGT genes in three tissues and under cold treatment suggested that trihelix genes were involved in diverse functions during D. officinale development and cold tolerance. This study provides novel insights into the phylogenetic relationships and functions of the D. officinaletrihelix genes, which will aid future functional studies investigating the divergent roles of trihelix genes belonging to other species.
Revisiting the Spatial Autoregressive Exponential Model for Counts and Other Nonnegative Variables, with Application to the Knowledge Production Function
Authors: Proença Isabel , Glórias Ludgero
Published: March 2021

This paper proposes a two-step pseudo-maximum likelihood estimator of a spatial autoregressive exponential model for counts and other nonnegative variables; it is particularly useful for dealing with zeros. It considers a model specification allowing us to easily determine the direct and indirect partial effects of explanatory variables (spatial spillovers and externalities). A simulation study shows that this method generally behaves better in terms of bias and root mean square error than existing procedures. An empirical example estimating a knowledge production function for the NUTS II European regions is analyzed. Results show that there is spatial dependence between regions on the creation of innovation, where regions less able to transform R&D expenses into innovation benefit from knowledge spatial spillovers through indirect effects. It is also concluded that the socioeconomic environment is important and that, unlike public R&D institutions, private companies are efficient at knowledge production.
A Multivariate VAR Model for Evaluating Sustainable Finance and Natural Resource Curse in West Africa: Evidence from Nigeria and Ghana
Authors: Shobande Olatunji Abdul , Enemona Joseph Onuche
Published: March 2021

The financial sector plays a critical role in society by mediating resources and assets within the economy between surplus and deficit units. Therefore, they have a great responsibility for the sustainability and prosperity of natural endowments. This study aimed to determine whether sustainable finance matters for the natural resource curse in Nigeria and Ghana. The empirical evidence is based on the Bayer and Hanck combined cointegration tests and Vector Autoregressive/Vector Error Correction Granger causality tests. The study highlights the importance of sustainable financing in natural resources management. Our findings also confirmed the existence of the financial resource curse in Nigeria and Ghana. Likewise, the medium through which sustainable finance affects the natural resource curse has been identified as the human development index (economic welfare). This current study has critical policy implications that suggest the need to establish a vibrant, sustainable financing strategy to assist domestic private investors with a strong interest in natural resource exploration and development, taking into account macroeconomic sustainability. Additionally, it also important to build a strong financial market which allows for policies designed to promote natural resource management.
Environmental Issues as Drivers for Food Choice: Study from a Multinational Framework
Authors: Guiné Raquel P. F. , Bartkiene Elena , Florença Sofia G. , Djekić Ilija , Bizjak Maša Černelič , Tarcea Monica , Leal Marcela , Ferreira Vanessa , Rumbak Ivana , Orfanos Panagiotis , Szűcs Viktória , Klava Dace , Korzeniowska Małgorzata , Isoldi Kathy , Correia Paula , Ferreira Manuela , Cardoso Ana Paula
Published: March 2021

This work intended to explore some motivations that influence people’s eating habits towards sustainability. This was an observational, cross-sectional study, carried out by questionnaire survey on a non-probabilistic sample of 10,067 participants from 13 countries (Argentina, Brazil, Croatia, Greece, Hungary, Latvia, Lithuania, Poland, Portugal, Serbia, Slovenia, Romania and United States). Results indicated that people prefer fresh local foods from the season, being important because it allows transportation and storage to be reduced, which in many cases implies refrigeration systems and consequent energy expenditure. Although people avoid food waste at home, the awareness for the waste at restaurants still needs to be improved. Consumers seem to prefer foods that have been produced and packed in sustainable ways but still give importance to the package—understandable for food products. The results also indicated significant differences in the food choice motivations between groups for all sociodemographic variables tested (age, sex, marital status, education, professional area, living environment and country), but the association was high only for variable country. Additionally, a tree classification analysis allowed to identify the relative importance of the influential variables on the sustainable food choices, with country being the most important, followed by age and sex. Additionally, discriminant function analysis allowed establishing a model for the relation between country and six variables accounting for preservation of biodiversity, respect for life, save natural resources, save energy, reduce industrial pollution and minimal packaging. Although with some limitations, this study brings valuable insight into some aspects linked with sustainable food choices on a number of countries and how people shape their food choices according to some sustainability issues.
Is Trade Credit a Sustainable Resource for Medium-Sized Italian Green Companies?
Authors: Arcuri Maria Cristina , Pisani Raoul
Published: March 2021

Medium-sized Enterprises (MEs) are a limited number of Small and Medium-sized Enterprises (SMEs) in EU-28 countries, but they contribute greatly to value added and employment. They are also key to pursuing sustainable local development in terms of green economic growth. Because trade credit is a crucial financial source for SMEs, this article investigates the importance of trade credit for Italian MEs, and particularly for ‘green’ MEs, rather than ‘non-green’ MEs. A panel analysis is applied to 101,250 observations over the period 2010–2019. We find that green MEs rely more on trade credit than non-green MEs. Moreover, trade credit is more important for younger, smaller, less profitable, and less liquid MEs. We further show that a substitution effect between trade and banking credit exists, and that the local development level affects the demand for trade credit. Our results demonstrate that trade credit supports sustainable development more than banking credit. Financial intermediaries should therefore include green parameters in the assessment of the creditworthiness of MEs, and policymakers should consider that trade credit and financial inclusion may be important in pursuing sustainable local development and economic growth.
Cultural Consumption and Citizen Engagement—Strategies for Built Heritage Conservation and Sustainable Development. A Case Study of Indore City, India
Authors: Billore Soniya
Published: March 2021

Cultural heritage is an invaluable asset of any city, region, or community and is an important component in the sustainable development of societies and economies. However, the role of cultural heritage has been understudied in terms of its social embeddedness and impact on social cohesion. This has led to a demand for more insights on how cultural heritage is conserved globally and more significantly via the role of societal stakeholders. Inclusive strategies allow diverse sections of a community to engage and enrich not only the anthropological interpretations of society but also support social stability and foster positive social change. This paper exemplifies how an inclusive approach was used to engage citizen engagement for the sustainable development of the built heritage in the city of Indore in central India. Best practices are presented through secondary data through various print and online sources relevant to the context. Open coding of secondary data has helped to identify strategic approaches and relationships that emerge as crucial to citizen engagement as presented in this study. The paper discusses strategies that, based on diversity and inclusivity, contribute to the enrichment of community knowledge, increased synergistic participation, and the enhancement of the sense of collective responsibility in cultural consumption.
Expectations and Needs of Estonian Health Sector SMEs from Living Labs in an International Context
Authors: Lepik Katri-Liis , Krigul Merle
Published: March 2021

Living labs bring experimentation out of otherwise closed R&D departments to real-life environments with the participation of users and stakeholders. Living labs have been established in all the Baltic Sea countries. They operate in many sectors, but the way services are structured varies widely. This study is focusing on the limited options of small and medium-sized enterprises (SMEs) from Baltic Sea states to test and validate their products and services both in local as well as international contexts, and resulting limited access to foreign markets. This study comprises a qualitative content analysis of interviews with SMEs to identify the internationalization potential of living labs. In particular, the authors have analyzed the needs, expectations and obstacles of SMEs in the healthcare sector in Estonia. The authors found that testing and validation activities in living labs would be beneficial mostly for SMEs ready for entering international markets. Other services offered by living labs could be of interest to SMEs considering entering new international markets but have not achieved validation.
The Differentiate Effect of Self-Efficacy, Motivation, and Satisfaction on Pre-Service Teacher Students’ Learning Achievement in a Flipped Classroom: A Case of a Modern Educational Technology Course
Authors: Zhao Li , Liu Xiaohong , Su Yu-Sheng
Published: March 2021

To analyze how variability changes over time can enhance the understanding of how learners’ self-efficacy, motivation, and satisfaction is controlled and why differences might exist among groups of individuals. Therefore, this study compared the effect of variability on pre-service teacher students in the flipped classroom approach with a course named modern educational technology (MET). In total, 77 students in two groups participated in this study. Learners in the experimental group received the flipped classroom treatment. Learners in the control group received the traditional lecture-centered instructional approach. The learning outcomes were evaluated by practice assignment, transfer assignment, and student perception survey. The survey includes the evaluation of learning satisfaction, self-efficacy, and learning motivation. Pre-test and post-test were conducted by the two groups. The data analysis results applied analysis of variance (ANOVA) or analysis of covariance (ANCOVA) and revealed that the experimental group displayed a better learning achievement than the control group. The experimental group participants’ perception also showed variability (i.e., learning satisfaction, self-efficacy, and learning motivation) was better than the control group. Considering the overall study results, the flipped classroom model can be applied in the pre-service teacher students’ modern educational technology course.
The Adaptive Reuse of Cultural Heritage in European Circular City Plans: A Systematic Review
Authors: Foster Gillian , Saleh Ruba
Published: March 2021

A new movement in urban environmental policy, the circular economy (CE), aims to change how Europeans consume and produce materials and energy. Cities are taking up the CE challenge. This research inquires whether the infant CE programs in European cities include cultural heritage and adaptive reuse of cultural heritage (ARCH) buildings. ARCH buildings exemplify the central principal of the CE, which is a temporally long service life with multiple uses for several generations of users. In addition, culture and cultural heritage buildings are established drivers of socioeconomic development, urban landscape, and identity. Hypothetically, cultural heritage and adaptive reuse of cultural heritage (ARCH) buildings should be prominently included in European cities’ CE programs, particularly those cities that are highly ranked on the 2019 European Cultural and Creative Cities Monitor (Monitor). To test this hypothesis, this study creates a novel dataset that profiles the existing circular city plans of 190 European cities included in the Monitor’s ranking. Contrary to the hypothesis, just seven percent of cities in the dataset include cultural heritage. European cities are missing an opportunity to achieve their CE goals and preserve their unique identities as embodied in the built environment.