bluuebunny/crossref_metadata_2025 huggingface dataset:
Improvement of Polymer Grade L-Lactic Acid Production Using Lactobacillus rhamnosus SCJ9 from Low-Grade Cassava Chips by Simultaneous Saccharification and Fermentation
Authors: Unban Kridsada , Puangkhankham Narongsak , Kanpiengjai Apinun , Govindarajan Rasiravathanahalli Kaveriyappan , Kalaimurugan Dharman , Khanongnuch Chartchai
Published: September 2020

The present study aims to examine the process for L-lactic acid production from low-grade cassava chips (LGC) using a two-step fermentation approach (TSF) and simultaneous saccharification and fermentation (SSF) by proficient, newly isolated Lactobacillus rhamnosus strain SCJ9. The optimized medium composition revealed by response surface methodology for TSF was 166 g/L LGC hydrolysate and 20 g/L yeast extract (YE), while other medium components were fixed (g/L) as follows: tween80 (2.0), (NH4)2HPO4 (2.0), CH3COONa∙3H2O (6.0), (NH4)2HC6H5O7 (2.0), MgSO4∙7H2O (0.5), and MnSO4∙H2O (0.3). Based on the optimization conditions, the maximum experimental L-lactic acid of 134.6 g/L was achieved at 60 h fermentation time with a production efficiency of 89.73%, 0.95 g/g yield and 2.24 g/L/h productivity. In contrast, L-lactic acid production by SSF under optimized concentrations of thermostable-α-amylase (AA) and glucoamylase (GA) gave maximum L-lactic acid of 125.79 g/L at only 36 h fermentation time which calculated to the production efficiency, yield and productivity of 83.86%, 0.93 g/g and 3.49 g/L/h, respectively. The L-lactic acid production obtained from SSF was significantly improved when compared to TSF based on lower enzyme loading usage, shorter hydrolysis time and increase in production efficiency and productivity. Furthermore, there were no significant differences in the production by SSF between experiments conducted in laboratory bottle and 10-L fermenter. The results indicated the success of up-scaling for L-lactic acid production by SSF which could be developed for a further pilot-scale production of L-lactic acid.
Applications of an Improved Aerodynamic Optimization Method on a Low Reynolds Number Cascade
Authors: Zhang Shuyi , Yang Bo , Xie Hong , Song Moru
Published: September 2020

The effect of cascade aerodynamic optimization on turbomachinery design is very significant. However, for most traditional cascade optimization methods, aerodynamic parameters are considered as boundary conditions and rarely directly used as the optimization variables to realize optimization. Given this problem, this paper proposes an improved cascade aerodynamic optimization method in which an incidence angle and nine geometric parameters are used to parameterize the cascade and one modified optimization algorithm is adopted to find the cascade with the optimal aerodynamic performance. The improved parameterization approach is based on the Non-Uniform Rational B-Splines (NURBS) method, the camber line superposing thickness distribution molding (CLSTDM) method, and the plane cascade design method. To rapidly and effectively find the cascade with the largest average lift-drag ratio within a certain range of incidence angles, modified particle swarm optimization combined with the modified very fast simulated annealing algorithm (PSO-MVFSA) is adopted. To verify the feasibility of the method, a cascade with NACA4412 and a practical cascade are optimized. It is found that the average lift-drag ratios of two optimal performance cascades are respectively increased by 13.38% and 15.21% in comparison to those of two original cascades. Meanwhile, through optimizing the practical cascade of the Blade D500, under different volume flow rates, the pressure coefficient of the optimized cascade is increased by an average of more than 6.12% compared to that of the prototype, and the average efficiency is increased by 11.15%. Therefore, this improved aerodynamic optimization method is reliable and feasible for the performance improvement of cascades with a low Reynolds number.
In Situ Observation for Deformation-Induced Martensite Transformation (DIMT) during Tensile Deformation of 304 Stainless Steel Using Neutron Diffraction. PART I: Mechanical Response
Authors: Onuki Yusuke , Sato Shigeo
Published: September 2020

304 stainless steel is one of the most common stainless steels due to its excellent corrosion resistance and mechanical properties. Typically, a good balance between ductility and strength derives from deformation-induced martensite transformation (DIMT), but this mechanism has not been fully explained. In this study, we conducted in situ neutron diffraction measurements during the tensile deformation of commercial 304 stainless steel (at room temperature) by means of a Time-Of-Flight type neutron diffractometer, iMATERIA (BL20), at J-PARC MLF (Japan Proton Accelerator Research Complex, Materials and Life Science Experimental Facility), Japan. The fractions of α′-(BCC) and ε-(HCP) martensite were quantitatively determined by Rietveld-texture analysis, as well as the anisotropic microstrains. The strain hardening behavior corresponded well to the microstrain development in the austenite phase. Hence, the authors concluded that the existence of martensite was not a direct cause of hardening, because the dominant austenite phase strengthened to equivalent values as in the martensite phase. Moreover, the transformation-induced plasticity (TRIP) mechanism in austenitic steels is different from that of low-alloy bainitic TRIP steels.
The Translation of Life: Thinking of Painting in Indian Buddhist Literature
Authors: Kachru Sonam
Published: September 2020

What are paintings? Is there a distinctive mode of experience paintings enable? What is the value of such experience? This essay explores such questions, confining attention for the most part to a few distinctive moments in Indian Buddhist texts. In particular, I focus on invocations of painting in figures of speech, particularly when paintings are invoked to make sense of events or experiences of particular importance. The aim is not to be exhaustive, but to suggest a meta-poetic orientation: On the basis of moments where authors think with figurations of painting, I want to suggest that in Buddhist texts one begins to find a growing regard for the possibilities of re-ordering and transvaluing sense experience. After suggesting the possibility of this on the basis of a preliminary consideration of some figures of speech invoking painting, this essay turns to the reconstruction of what I call aesthetic stances to make sense of the idea of new possibilities in sense experience. I derive the concept of “aesthetic stances” on the basis of a close reading of a pivotal moment in one Buddhist narrative, the defeat of Māra in The Legend of Aśoka.
Was a Sacred Curtain (Parokhet) Depicted on Portable Shrines in the Ancient Near East?
Authors: Mumcuoglu Madeleine , Garfinkel Yosef
Published: September 2020

The Parokhet, or sacred curtain, was an important item of cultic paraphernalia in the ancient Near East. It is known from the Sumerian and Akkadian texts, the biblical tradition, the Second Temple in Jerusalem, Greek temples, and synagogues of the Roman and Byzantine eras, and is still in use today. We suggest that such a sacred curtain is depicted on several of the miniature clay objects known as portable shrines. In Egypt, thanks to the dry climate, a miniature curtain of this kind has indeed been preserved in association with a portable shrine. Depictions of shrines on Egyptian sacred barks also include life-size curtains.
Application of Spectral Mixture Analysis to Vessel Monitoring Using Airborne Hyperspectral Data
Authors: Park Jae-Jin , Kim Tae-Sung , Park Kyung-Ae , Oh Sangwoo , Lee Moonjin , Foucher Pierre-Yves
Published: September 2020

As marine transportation has increased in coastal regions, maritime accidents associated with vessels have steadily increased. Remotely sensed satellite or airborne images can aid rapid vessel monitoring over wide areas at high resolutions. In this study, airborne hyperspectral experiments were performed to detect marine vessels mainly including fishing boat and yacht by applying pixel-based mixture techniques and to estimate the size of the vessels through an objective ellipse fitting method. Various spectral libraries of marine objects and seawaters were constructed through in-situ experiments for spectral analysis of the internal structures of vessels. The hyperspectral images were dimensionally reduced through principal component analysis. Several hyperspectral mixture algorithms, such as N-FINDR, pixel purity index (PPI), independent component analysis (ICA), and vertex component analysis (VCA), were used for the detection of vessels. The N-FINDR and VCA techniques presented a total of 14 vessels, the ICA technique detected seven vessels, and the PPI technique detected two vessels. The pixel-based probability of detection (POD) and false alarm ratio (FAR) for all 14 vessels were 96.40% and 4.30%, respectively. The sizes of the vessels were estimated by extracting the boundaries of the vessels through a two-dimensional gradient and applying the ellipse fitting method. Compared with the digital mapping camera (DMC) images with resolutions of 0.10 m, the root-mean-square errors of the length and width of the vessels were approximately 1.19 m and 0.81 m, respectively. The application of spectral mixing methods provided a high probability of detecting the objects, as well as the overall structures of the decks of the vessels.
On the Characterization and Forecasting of Ground Displacements of Ocean-Reclaimed Lands
Authors: Ding Jingzhao , Zhao Qing , Tang Maochuan , Calò Fabiana , Zamparelli Virginia , Falabella Francesco , Liu Min , Pepe Antonio
Published: September 2020

In this work, we study ground deformation of ocean-reclaimed platforms as retrieved from interferometric synthetic aperture radar (InSAR) analyses. We investigate, in particular, the suitability and accuracy of some time-dependent models used to characterize and foresee the present and future evolution of ground deformation of the coastal lands. Previous investigations, carried out by the authors of this paper and other scholars, related to the zone of the ocean-reclaimed lands of Shanghai, have already shown that ocean-reclaimed lands are subject to subside (i.e., the ground is subject to settling down due to soil consolidation and compression), and the temporal evolution of that deformation follows a certain predictable model. Specifically, two time-gapped SAR datasets composed of the images collected by the ENVISAT ASAR (ENV) from 2007 to 2010 and the COSMO-SkyMed (CSK) sensors, available from 2013 to 2016, were used to generate long-term ground displacement time-series using a proper time-dependent geotechnical model. In this work, we use a third SAR data set consisting of Radarsat-2 (RST-2) acquisitions collected from 2012 to 2016 to further corroborate the validity of that model. As a result, we verified with the new RST-2 data, partially covering the gap between the ENV and CSK acquisitions, that the adopted model fits the data and that the model is suitable to perform future projections. Furthermore, we extended these analyses to the area of Pearl River Delta (PRD) and the city of Shenzhen, China. Our study aims to investigate the suitability of different time-dependent ground deformation models relying on the different geophysical conditions in the two areas of Shanghai and Shenzhen, China. To this aim, three sets of SAR data, collected by the ENV platform (from both ascending and descending orbits) and the Sentinel-1A (S1A) sensor (on ascending orbits), were used to obtain the ground displacement time-series of the Shenzhen city and its surrounding region. Multi-orbit InSAR data products were also combined to discriminate the up–down (subsidence) ground deformation time-series of the coherent points, which are then used to estimate the parameters of the models adopted to foresee the future evolution of the land-reclaimed ground consolidation procedure. The exploitation of the obtained geospatial data and products are helpful for the continuous monitoring of coastal environments and the evaluation of the socio-economical impacts of human activities and global climate change.
Inter-Comparison of Normalized Difference Vegetation Index Measured from Different Footprint Sizes in Cropland
Authors: Ryu Jae-Hyun , Na Sang-Il , Cho Jaeil
Published: September 2020

Remote sensing techniques using visible and near-infrared wavelengths are useful for monitoring terrestrial vegetation. The normalized difference vegetation index (NDVI) is a widely used proxy of vegetation conditions, and it has been measured at various footprint sizes using satellite, unmanned aerial vehicle (UAV), and ground-installed sensors. The goal of this study was to analyze the spatial characteristics of NDVI data by comparing the values obtained at different footprint sizes. In particular, the NDVI was evaluated in garlic and onion fields that featured ridges and furrows. The evaluation was performed using data from a leaf spectrometer, field spectrometers, ground-installed spectral reflectance sensors, a multispectral camera onboard a UAV, and Sentinel-2 satellites. The correlation coefficients between NDVIs evaluated from the various sensors (excluding the satellite-mounted sensors) ranged from 0.628 to 0.944. The UAV-based NDVI (NDVIUAV) exhibited the lowest root mean square error (RMSE = 0.088) when compared with field spectrometer data. On the other hand, the satellite-based NDVI data (NDVISentinel-2) were poorly correlated with those obtained from the other sensors as a result of the footprint mismatch. However, by upscaling the NDVIUAV data to the pixel size of Sentinel-2, the comparison was improved, and the following statistics were obtained: correlation coefficient: 0.504–0.785; absolute bias: 0.048–0.078; RMSE: 0.063–0.094. According to the aforementioned results, ground-based NDVI data can be used to validate NDVIUAV data without further processing and NDVIUAV data can be used to validate NDVISentinel-2 data after upscaling to the Sentinel-2 pixel size. Overall, the results presented in this study may be helpful to understand and integrate NDVI data at different spatial scales.
RGB Image-Derived Indicators for Spatial Assessment of the Impact of Broadleaf Weeds on Wheat Biomass
Authors: Gée Christelle , Denimal Emmanuel
Published: September 2020

In precision agriculture, the development of proximal imaging systems embedded in autonomous vehicles allows to explore new weed management strategies for site-specific plant application. Accurate monitoring of weeds while controlling wheat growth requires indirect measurements of leaf area index (LAI) and above-ground dry matter biomass (BM) at early growth stages. This article explores the potential of RGB images to assess crop-weed competition in a wheat (Triticum aestivum L.) crop by generating two new indicators, the weed pressure (WP) and the local wheat biomass production (δBMc). The fractional vegetation cover (FVC) of the crop and the weeds was automatically determined from the images with a SVM-RBF classifier, using bag of visual word vectors as inputs. It is based on a new vegetation index called MetaIndex, defined as a vote of six indices widely used in the literature. Beyond a simple map of weed infestation, the map of WP describes the crop-weed competition. The map of δBMc, meanwhile, evaluates the local wheat above-ground biomass production and informs us about a potential stress. It is generated from the wheat FVC because it is highly correlated with LAI (r2 = 0.99) and BM (r2 = 0.93) obtained by destructive methods. By combining these two indicators, we aim at determining whether the origin of the wheat stress is due to weeds or not. This approach opens up new perspectives for the monitoring of weeds and the monitoring of their competition during crop growth with non-destructive and proximal sensing technologies in the early stages of development.
How Does Spartina alterniflora Invade in Salt Marsh in Relation to Tidal Channel Networks? Patterns and Processes
Authors: Sun Limin , Shao Dongdong , Xie Tian , Gao Weilun , Ma Xu , Ning Zhonghua , Cui Baoshan
Published: September 2020

Rapid invasion of Spartina alterniflora in coastal wetlands throughout the world has attracted much attention. Some field and imagery evidence has shown that the landward invasion of S. alterniflora follows the tidal channel networks as the main pathway. However, the specific patterns and processes of its invasion in salt marshes in relation to tidal channel networks are still unclear. Based on yearly satellite images from 2010 to 2018, we studied the patterning relationship between tidal channel networks and the invasion of S. alterniflora at the south bank of the Yellow River Estuary (SBYRE). At the landscape (watershed and cross-watershed) scale, we analyzed the correlation between proxies of tidal channel network drainage efficiency (unchanneled flow lengths (UFL), overmarsh path length (OPL), and tidal channels density (TCD)) and spatial distribution of S. alterniflora. At the local (channel) scale, we examined the area and number of patches of S. alterniflora in different distance buffer zones outward from the tidal channels. Our results showed that, overall, the invasion of S. alterniflora had a strong association with tidal channel networks. Watershed with higher drainage efficiency (smaller OPL) attained larger S. alterniflora area, and higher-order (third-order and above) channels tended to be the main pathway of S. alterniflora invasion. At the local scale, the total area of S. alterniflora in each distance buffer zones increased with distance within 15 m from the tidal channels, whereas the number of patches decreased with distance as expansion stabilized. Overall, the S. alterniflora area within 30 m from the tidal channels remained approximately 14% of its entire distribution throughout the invasion. The results implicated that early control of S. alterniflora invasion should pay close attention to higher-order tidal channels as the main pathway
Modeling Spatio-Temporal Land Transformation and Its Associated Impacts on land Surface Temperature (LST)
Authors: Mumtaz Faisal , Tao Yu , de Leeuw Gerrit , Zhao Limin , Fan Cheng , Elnashar Abdelrazek , Bashir Barjeece , Wang Gengke , Li LingLing , Naeem Shahid , Arshad Arfan , Wang Dakang
Published: September 2020

Land use land cover (LULC) of city regions is strongly affected by urbanization and affects the thermal environment of urban centers by influencing the surface temperature of core city areas and their surroundings. These issues are addressed in the current study, which focuses on two provincial capitals in Pakistan, i.e., Lahore and Peshawar. Using Landsat data, LULC is determined with the aim to (a) examine the spatio-temporal changes in LULC over a period of 20 years from 1998 to 2018 using a CA-Markov model, (b) predict the future scenarios of LULC changes for the years 2023 and 2028, and (c) study the evolution of different LULC categories and investigate its impacts on land surface temperature (LST). The results for Peshawar city indicate the significant expansion in vegetation and built-up area replacing barren land. The vegetation cover and urban area of Peshawar have increased by 25.6%, and 16.3% respectively. In contrast, Lahore city urban land has expanded by 11.2% while vegetation cover decreased by (22.6%). These transitions between LULC classes also affect the LST in the study areas. Transformation of vegetation cover and water surface into built-up areas or barren land results in the increase in the LST. In contrast, the transformation of urban areas and barren land into vegetation cover or water results in the decrease in LST. The different LULC evolutions in Lahore and Peshawar clearly indicate their effects on the thermal environment, with an increasing LST trend in Lahore and a decrease in Peshawar. This study provides a baseline reference to urban planners and policymakers for informed decisions.
Inter-Calibration of AMSU-A Window Channels
Authors: Yang Wenze , Meng Huan , Ferraro Ralph R. , Chen Yong
Published: September 2020

More than one decade of observations from the Advanced Microwave Sounding Unit-A (AMSU-A) onboard the polar-orbiting satellites NOAA-15 to NOAA-19 and European Meteorological Operational satellite program-A (MetOp-A) provided global information on atmospheric temperature profiles, water vapor, cloud, precipitation, etc. These observations were primarily intended for weather related prediction and applications, however, in order to meet the requirements for climate application, further reprocessing must be conducted to first eliminate any potential satellites biases. After the geolocation and cross-scan bias corrections were applied to the dataset, follow-on research focused on the comparison amongst AMSU-A window channels (e.g., 23.8, 31.4, 50.3 and 89.0 GHz) from the six different satellites to remove any inter-satellite inconsistency. Inter-satellite differences can arise from many error sources, such as bias drift, sun-heating-induced instrument variability in brightness temperatures, radiance dependent biases due to inaccurate calibration nonlinearity, etc. The Integrated microwave inter-calibration approach (IMICA) approach was adopted in this study for inter-satellite calibration of AMSU-A window channels after the appropriate standard deviation (STD) thresholds were identified to restrict Simultaneous Nadir Overpass (SNO) data for window channels. This was a critical step towards the development of a set of fundamental and thematic climate data records (CDRs) for hydrological and climatological applications. NOAA-15 served as the main reference satellite for this study. For ensuing studies that expand to beyond 2015, however, it is recommended that a different satellite be adopted as the reference due to concerns over potential degradation of NOAA-15 AMSU-A.
A Remotely Sensed Assessment of Surface Ecological Change over the Gomishan Wetland, Iran
Authors: Qureshi Salman , Alavipanah Seyed Kazem , Konyushkova Maria , Mijani Naeim , Fathololomi Solmaz , Firozjaei Mohammad Karimi , Homaee Mehdi , Hamzeh Saeid , Kakroodi Ata Abdollahi
Published: September 2020

Due to the excessive use of natural resources in the contemporary world, the importance of ecological and environmental condition modeling has increased. Wetlands and cities represent the natural and artificial strategic areas that affect ecosystem conditions. Changes in the ecological conditions of these areas have a great impact on the conditions of the global ecosystem. Therefore, modeling spatiotemporal variations of the ecological conditions in these areas is critical. This study was aimed at comparing degrees of variation among surface ecological conditions due to natural and unnatural factors. Consequently, the surface ecological conditions of Gomishan city and Gomishan wetland in Iran were modeled for a period of 30 years, and the spatiotemporal variations were evaluated and compared with each other. To this end, 20 Landsat 5, 7, and 8, and 432 Moderate Resolution Imaging Spectroradiometer (MODIS), monthly land surface temperature (LST) (MOD11C3) and normalized difference vegetation index (NDVI) (MOD13C3) products were utilized. The surface ecological conditions were modeled according to the Remote Sensing-based Ecological Index (RSEI), and the spatiotemporal variation of the RSEI values in the study area (Gomishan city, Gomishan wetland) were evaluated and compared with each other. According to MODIS products, the mean of the LST and NDVI variance values for the study area (Gomishan city, Gomishan wetland) were obtained to be 6.5 °C (2.1, 12.1) and 0.009 (0.005, 0.013), respectively. The highest LST and NDVI temporal variations were found for Gomishan wetland near the Caspian Sea. According to Landsat images, Gomishan wetland and Gomishan city have the highest and lowest temporal variations in surface biophysical characteristics, respectively. The mean RSEI for the study area (Gomishan city, Gomishan wetland) was 0.43 (0.65, 0.29), respectively. Additionally, the mean Coefficient of Variation (CV) of RSEI for the study area (Gomishan city, Gomishan wetland) was 0.10 (0.88, 0.51), respectively. The surface ecological conditions of Gomishan city were worse than those of the Gomishan wetland at all dates. Temporal variations in the surface ecological conditions of Gomishan wetland were greater than those of the study area and Gomishan city. These results can provide useful and effective information for environmental planning and decision-making to improve ecological conditions, protect the environment, and support sustainable ecosystem development.
MultiFuzz: A Coverage-Based Multiparty-Protocol Fuzzer for IoT Publish/Subscribe Protocols
Authors: Zeng Yingpei , Lin Mingmin , Guo Shanqing , Shen Yanzhao , Cui Tingting , Wu Ting , Zheng Qiuhua , Wang Qiuhua
Published: September 2020

The publish/subscribe model has gained prominence in the Internet of things (IoT) network, and both Message Queue Telemetry Transport (MQTT) and Constrained Application Protocol (CoAP) support it. However, existing coverage-based fuzzers may miss some paths when fuzzing such publish/subscribe protocols, because they implicitly assume that there are only two parties in a protocol, which is not true now since there are three parties, i.e., the publisher, the subscriber and the broker. In this paper, we propose MultiFuzz, a new coverage-based multiparty-protocol fuzzer. First, it embeds multiple-connection information in a single input. Second, it uses a message mutation algorithm to stimulate protocol state transitions, without the need of protocol specifications. Third, it uses a new desockmulti module to feed the network messages into the program under test. desockmulti is similar to desock (Preeny), a tool widely used by the community, but it is specially designed for fuzzing and is 10x faster. We implement MultiFuzz based on AFL, and use it to fuzz two popular projects Eclipse Mosquitto and libCoAP. We reported discovered problems to the projects. In addition, we compare MultiFuzz with AFL and two state-of-the-art fuzzers, MOPT and AFLNET, and find it discovering more paths and crashes.
The Impact of Rate Adaptation Algorithms on Wi-Fi-Based Factory Automation Systems
Authors: Fedullo Tommaso , Tramarin Federico , Vitturi Stefano
Published: September 2020

Factory automation systems based on the IEEE 802.11 Wi-Fi standard may benefit from its Multi-Rate Support (MRS) feature, which allows for dynamically selecting the most suitable transmission rate for the targeted application context. The MRS is implemented by means of rate adaptation algorithms (RAAs), which has already demonstrated to be effective to improve both timeliness and reliability, which are typically strict requirements of industrial real-time communication systems. Indeed, some of such algorithms have been specifically conceived for reliable real-time communications. However, the computational complexity of such algorithms has not been effectively investigated yet. In this paper, we address such an issue, particularly focusing on the execution times of some specific rate adaptation algorithms, as well as on their impact on the automation tasks. In this respect, after a formal description of the algorithms, we present the outcomes of an extensive experimental session, which includes practical measurements and realistic simulations. The obtained results are encouraging, since the measured execution times indicate that rate adaptation algorithms can be profitably adopted by industrial automation systems, allowing for improving their reliability and timeliness without impacting on the overall performance.
A Modified Kalman Filter for Integrating the Different Rate Data of Gyros and Accelerometers Retrieved from Android Smartphones in the GNSS/IMU Coupled Navigation
Authors: Yan Wenlin , Zhang Qiuzhao , Wang Lijuan , Mao Ying , Wang Aisheng , Zhao Changsheng
Published: September 2020

Recent study indicates that by using the inertial measurement unit (IMU) sensors inside smartphones, we can obtain similar navigation solutions to the professional ones. However, the sampling rates of the gyros and accelerometers inside some types of smartphones are not set in the same frequencies, i.e., the gyros of “Huawei p40” are in 50 Hz while the accelerometer is 100 Hz. The conventional method is resampling the higher frequency to the lower frequency ones, which means the resampled accelerometer will lose half frequency observations. In this work, a modified Kalman filter was proposed to integrate all these different rate IMU data in the GNSS/IMU-smartphone coupled navigation. To validate the proposed method, a terrestrial test with two different types of android smartphones was done. With the proposed method, a slight improvement of the attitude solutions can be seen in the experiments under the GNSS open-sky condition, and the obvious improvement of the attitude solutions can be witnessed at the simulated GNSS denied situation. The improvements by 45% and 23% of the horizontal position accuracy can be obtained from the experiments under the GNSS outage of 50 s in a straight line and 30 s in a turning line, respectively.
Deep-Net: A Lightweight CNN-Based Speech Emotion Recognition System Using Deep Frequency Features
Authors: Anvarjon Tursunov , Mustaqeem  , Kwon Soonil
Published: September 2020

Artificial intelligence (AI) and machine learning (ML) are employed to make systems smarter. Today, the speech emotion recognition (SER) system evaluates the emotional state of the speaker by investigating his/her speech signal. Emotion recognition is a challenging task for a machine. In addition, making it smarter so that the emotions are efficiently recognized by AI is equally challenging. The speech signal is quite hard to examine using signal processing methods because it consists of different frequencies and features that vary according to emotions, such as anger, fear, sadness, happiness, boredom, disgust, and surprise. Even though different algorithms are being developed for the SER, the success rates are very low according to the languages, the emotions, and the databases. In this paper, we propose a new lightweight effective SER model that has a low computational complexity and a high recognition accuracy. The suggested method uses the convolutional neural network (CNN) approach to learn the deep frequency features by using a plain rectangular filter with a modified pooling strategy that have more discriminative power for the SER. The proposed CNN model was trained on the extracted frequency features from the speech data and was then tested to predict the emotions. The proposed SER model was evaluated over two benchmarks, which included the interactive emotional dyadic motion capture (IEMOCAP) and the berlin emotional speech database (EMO-DB) speech datasets, and it obtained 77.01% and 92.02% recognition results. The experimental results demonstrated that the proposed CNN-based SER system can achieve a better recognition performance than the state-of-the-art SER systems.
Sensor Fusion Algorithm Using a Model-Based Kalman Filter for the Position and Attitude Estimation of Precision Aerial Delivery Systems
Authors: Garcia-Huerta Raul A. , González-Jiménez Luis E. , Villalon-Turrubiates Ivan E.
Published: September 2020

In this research, we focus on the use of Unmanned Aerial Vehicles (UAVs) for the delivery of payloads and navigation towards safe-landing zones, specifically on the modeling of flight dynamics of lightweight vehicles denoted Precision Aerial Delivery Systems (PADSs). While a wide range of nonlinear models has been developed and tested on high-end applications considering various degrees of freedom (DOF), linear models suitable for low-cost applications have not been explored thoroughly. In this study, we propose and compare two linear models, a linearized version of a 6-DOF model specifically developed for micro-lightweight systems, and an alternative model based on a double integrator. Both linear models are implemented with a sensor fusion algorithm using a Kalman filter to estimate the position and attitude of PADSs, and their performance is compared to a nonlinear 6-DOF model. Simulation results demonstrate that both models, when incorporated into a Kalman filter estimation scheme, can determine the flight dynamics of PADSs during smooth flights. While it is validated that the double integrator model can adequately operate under the proposed estimation scheme for up to small acceleration changes, the linearized model proves to be capable of reproducing the nonlinear model characteristics even during moderately steep turns.
Sensor Fusion in Assistive and Rehabilitation Robotics
Authors: Novak Domen , Riener Robert
Published: September 2020

As the world’s population gradually grows older, more and more adults are experiencing sensory–motor disabilities due to stroke, traumatic brain injury, spinal cord injury and other diseases [...]
Fiber Bragg Grating Sensors for Pile Jacking Monitoring in Clay Soil
Authors: Wang Yonghong , Liu Xueying , Zhang Mingyi , Bai Xiaoyu , Mou Ben
Published: September 2020

The small deformation of the model pile in a pile jacking test makes its accurate measurement very difficult. Based on the installation method of clamping at both ends, a sensitized miniature fiber Bragg grating (FBG) strain sensor was developed to measure the pile strain of small-size model piles. This study investigated the working principle of the sensitized miniature FBG sensor and analyzed the strain transfer characteristics of the sensor by calibration test. The lateral resistance and the earth plug resistance of the model pile were measured accurately by the grooves embedded in the outer tube of the double-wall opening model pile and the sensors directly pasted on the surface of the inner tube. The results of this study show that the sensitized miniature FBG strain sensor has the advantages of high sensitivity, strong interference resistance, and high test accuracy. The FBG strain sensor was completely fixed on the pile by clamping supports at both ends, and the strain measured using the FBG strain sensor was found to be consistent with the pile deformation.
Increasing Resilience of the UK Fresh Fruit and Vegetable System to Water-Related Risks
Authors: Zurek Monika , Garbutt George , Lieb Theresa , Hess Tim , Ingram John
Published: September 2020

The many economic, regulatory and environmental pressures on growing, processing, distributing and retailing UK-produced fresh fruit and vegetables (FF&V) are managed by a complex set of actors before reaching the consumer. Much of this production takes place in the driest parts of the country which are characterised as “water scarce”. While physical risk is a key component of water-related risks to growers, different actors in the system face other types of risk, such as supply chain risks, food safety risks, reputational risks and/or regulatory risks. In this paper we reveal how different types of actors in the UK FF&V system perceive and frame water-related risks, what risk management strategies they employ and how they envision a FF&V system more resilient to water-related risks. Using interviews with actors from across the system, as well as governmental and nongovernmental actors influencing the system, we unpack the complex nature of the FF&V system. This provides insights into the different ways system actors assemble around water-risk and highlights that, if resilience-building activities at the individual actor level are not coordinated, there is a high risk that they are undermining overall system resilience.
On-Site Use of Plant Litter and Yard Waste as Mulch in Gardening and Landscaping Systems
Authors: Stavi Ilan
Published: September 2020

Plant litter, such as fallen leaves, branch trimmings, and other yard waste, plays important roles in both natural and man-made ecosystems. However, due to common aesthetic perceptions, land-owners or managers of many residential gardening and municipal landscaping systems consider these organic residues a burden, and therefore, clear them from the ground and dispose of them off-site. The removal of these organic resources increases the system’s environmental footprint, decreases its sustainability, and negates the provision of important ecosystem services. At the same time, retaining these organic materials on-site could provide the system with substantial benefits. The most obvious effect is the ground surface shading, which decreases direct solar radiation to the soil, lowers soil temperature, lessens evaporation rates, decreases risk of soil salinization, and improves water-use efficiency. Ground surface mulching likewise prevents the raindrop splash impact, negates the formation of sealed mechanical crusts, improves water infiltrability, and reduces water runoff and soil erosion. Another benefit is the on-site decomposition of organic materials, which improves soil quality by elevating organic carbon concentration and contributing to nutrient cycling. Vegetation patches in such systems encompass "engineered fertility islands", which can be defined as highly productive, healthy, and functioning habitats. Further, over time, these systems require less maintenance. This management practice is crucial for tree- or shrub-dominated gardening and landscaping systems in drylands, where water availability is the major limiting factor of vegetation growth. However, global climate change, in which extended parts of the world experience increasing temperatures and decreasing precipitation rates, makes this practice relevant for other climatic regions as well.
Exposure Level of Neonicotinoid Insecticides in the Food Chain and the Evaluation of Their Human Health Impact and Environmental Risk: An Overview
Authors: Zhao Yuanyuan , Yang Jiawen , Ren Jinbo , Hou Yilin , Han Zhenzhen , Xiao Jiapeng , Li Yu
Published: September 2020

Neonicotinoid insecticides (neonics) were the most rapidly growing class of insecticides over the past few decades, and are used mainly for vegetables, fruits, and grains. Although neonics exhibit lower toxicity in mammals and humans compared to traditional insecticides, increasing numbers of studies are demonstrating that neonics may accumulate in the food chain and environmental media. Long-term exposure to neonics may raise potential risks to animals and even to humans. The present report reviews the development, application, and prohibition of neonics in the farmland ecosystem, and summarizes the exposure level and harmful effects of these insecticides in the food chain. In addition, the present review analyzes and summarizes the evaluation of the human health impact and environmental risk of the neonics, and overviews the unresolved problems and future research directions in this field. The aim of the present report was to review the exposure level, potential toxicity, human health impact, and environmental risk assessment of neonics in various media in order to provide reliable technical support for strengthening the environmental and food safety supervision and green pesticide designing.
Research and Development as a Moderating Variable for Sustainable Economic Performance: The Asian, European, and Kuwaiti Models
Authors: Salman Ahmad , Al-Hemoud Ali , Fakhraldeen Saja A. , Al-Nashmi Maha , AlFadhli Suad M. , Chun Sungsoo
Published: September 2020

The research and development (R&D) expenditure in Kuwait is insufficient to lead to innovation and a knowledge economy. Investment in R&D has been shown to sustain elevated economic performance. The objective of this study is to explore the association between three competing dimensions of R&D indicators that lead to sustainable economic performance within any given country, namely, R&D expenditure, the number of researchers, and the number of patent rights, using time-series data collected over a 20-year period (1996–2016) by the World Bank Group. R&D indicators were compared between high- and middle-income countries including models from Asian (South Korea, Singapore, and Malaysia) and European (Finland and Ireland) countries as well as the State of Kuwait. Moreover, a case study describing R&D investments in Kuwait is presented. Overall, the results reveal higher R&D spending, number of researchers, and gross domestic product (GDP) per capita for the Asian and European models. Current R&D expenditure in Kuwait is estimated at 0.08% of GDP (2016), which is significantly lower than the mean of the middle-income countries (1.58%). Furthermore, the number of researchers (per million) in Kuwait (386) is less than half of the mean number of researchers in middle-income countries (775) (2015). Low R&D investments in the State of Kuwait has gradually led to a decreased GDP per capita. Regression analysis shows that GDP per capita can be predicted solely based on the number of researchers (beta = 0.780, R2 = 0.608). The number of researchers is the most crucial variable to predict GDP per capita, and the R&D expenditure is a good indicator of the number of researchers. These findings offer invaluable insight into the sustainable development goals (SDG 9). To our knowledge, this paper presents the first application of the effect of R&D on sustainable economic performance with reference to the SDG target 9.5 “Research & Development”. Thus, in order to enhance scientific research (both academic, professional, and industrial), countries need to increase the number of researchers, and these actions are necessary to introduce sustainable growth to GDP.
Exploring Plant-Based Ethnomedicine and Quantitative Ethnopharmacology: Medicinal Plants Utilized by the Population of Jasrota Hill in Western Himalaya
Authors: Singh Bishander , Singh Bikarma , Kishor Anand , Singh Sumit , Bhat Mudasir Nazir , Surmal Opender , Musarella Carmelo Maria
Published: September 2020

Plants and natural products have played a significant role in curing and preventing a variety of ailments occurring in humans and animals, and continue to provide new bioactive leads for researchers in therapeutic discovery. This study was conducted with the aim to identify and document local healers’ practices of treating human diseases and quantitatively document indigenous knowledge of medicinal plants, as well as to highlight the species of public interest for bioprospecting potential. A total of 17 field tours were carried out in 12 regions of Jasrota hill and its adjoining areas of Himalaya. Informants (113) were interviewed using semi-structured interviews and discussions and local guided collections. The results were analyzed using ethnobotanical indices—use-reports (URs) and the informant consensus factor (ICF)—and the data were statistically analyzed. The ethnopharmacological uses of 121 plant species belonging to 105 genera and 53 families were reported for use as medicine for treating 93 types of ailments. A total of 4987 URs were mentioned by 113 informants. Fabaceae (90.09%) and Asteraceae (6.62%) were the most represented families. Herbs (46.28%) were the primary sources of medicine, decoction (33.88%) was the most common use method for utilization, and leaves (43.80%) were the most frequently used plant parts. The ICF values ranged from 0.667 to 0.974, with the highest number of species (1314UR, 55 species) being used for the treatment of gastrointestinal ailments (GIA), followed by dermatological disorders (38 species). This result showed that the exchange of knowledge could be evident among the different communities, and their medicinal uses and practices could be correlated.
Analysis of a Signalized Intersection with Dynamic Use of the Left-Turn Lane for Opposite through Traffic
Authors: Zheng Yongtao , Hua Xuedong , Wang Wei , Xiao Jialiang , Li Dongya
Published: September 2020

For signalized intersections with a quantitative imbalance between the approach and exit lanes, this study proposes a method for the dynamic use of the left-turn lane for opposite through traffic to improve the efficiency of the signalized intersection. The complete scheme of this method mainly consists of three parts: the location routes of the dynamic lane, the temporal scheme, and the spatial scheme. To demonstrate the effectiveness of this method, a simulation scheme comparing the intersection with and without the dynamic lane is designed using VISSIM. The parameters of the simulation model, including the traffic simulation environment parameters and built-in VISSIM models, are calibrated by the field data collected from an intersection in Nanjing, P. R. China. The results of the simulation indicate that this method decreases the average delay and average queue length of the intersection effectively for the intersection with a quantitative imbalance between the approach and exit lanes under the conditions of different through volumes or left-turn ratios. The maxima were 46.9% (average delay) and 68.3% (average queue length) for all situations. Lastly, some suggestions are presented for the application of this method.
The Relationship between Self-Esteem and Achievement Goals in University Students: The Mediating and Moderating Role of Defensive Pessimism
Authors: Ferradás María del Mar , Freire Carlos , Núñez José Carlos , Regueiro Bibiana
Published: September 2020

Although achievement goals have been the subject of much study about their implications for learning and performance, interest has been less marked in understanding their precursors, particularly those linked to students’ personal characteristics. In this study, we examine the role of a defensive pessimism strategy as a mediator and moderator of the relationships between self-esteem and achievement goals in a sample of 1028 university students. Analysis of mediation and moderation was performed using the PROCESS macro within SPSS. The results showed that defensive pessimism partially mediates and moderates the effect of self-esteem on approach goals (learning and performance). We found no significant mediation or moderation effect for defensive pessimism in the relationship between self-esteem and performance-avoidance goals. These findings suggest that defensive pessimism is an effective strategy to encourage motivational involvement in students with low self-esteem in the academic context.
Aligning Intentions with Community: Graduate Students Reflect on Collaborative Methodologies with Indigenous Research Partners
Authors: Wray Kristine , Soukhaphon Akarath , Parlee Brenda , D’Souza Amabel , Freitas Carolina , Heredia Iria , Martin Chelsea , Oloriz Carrie , Proverbs Tracey , Spicer Neal
Published: September 2020

Collaborative and community-based research (CCBR) is well defined and discussed in the literature; however, there are few discussions about graduate students doing CCBR with Indigenous communities. This project report features insights from nine graduate students attending six universities in Canada, the United States, and Brazil. These students are a part of a multi-year research partnership grant involving fishing communities from three major watersheds, the Mackenzie River Basin, the Amazon River Basin, and the lower Mekong River Basin. Each student engaged in collaborative research around the themes of Indigenous fishing livelihoods and the role of local and traditional knowledge in river basin governance. This project report presents reflections of graduate students on developing relationships and enacting CCBR during the following three stages of research with Indigenous communities: research project design, research project implementation, and post-project engagement. Best practices have been developed from graduate student reflections on issues, challenges, and needs of graduate students doing CCBR. The findings suggest that a diversity of factors contribute to effective CCBR. This includes the needs and interests of the community partner, the quality of supervisor support, the skillset of the student, their disciplinary background, and their capacity to work in complex sociopolitical contexts.