bluuebunny/crossref_metadata_2025 huggingface dataset:
Essential Oil-Loaded NLC for Potential Intranasal Administration
Authors: Bonaccorso Angela , Cimino Cinzia , Manno Daniela Erminia , Tomasello Barbara , Serra Antonio , Musumeci Teresa , Puglisi Giovanni , Pignatello Rosario , Carbone Claudia
Published: July 2021

Complementary and alternative medicines represent an interesting field of research on which worldwide academics are focusing many efforts. In particular, the possibility to exploit pharmaceutical technology strategies, such as the nanoencapsulation, for the delivery of essential oils is emerging as a promising strategy not only in Italy but also all over the world. The aim of this work was the development of nanostructured lipid carriers (NLC) for the delivery of essential oils (Lavandula, Mentha, and Rosmarinus) by intranasal administration, an interesting topic in which Italian contributions have recently increased. Essential oil-loaded NLC, projected as a possible add-on strategy in the treatment of neurodegenerative diseases, were characterized in comparison to control formulations prepared with Tegosoft CT and Neem oil. Homogeneous (polydispersity index, PDI < 0.2) nanoparticles with a small size (<200 nm) and good stability were obtained. Morphological and physical-chemical studies showed the formation of different structures depending on the nature of the liquid oil component. In particular, NLC prepared with Lavandula or Rosmarinus showed the formation of a more ordered structure with higher cytocompatibility on two cell lines, murine and human fibroblasts. Taken together, our preliminary results show that optimized positively charged NLC containing Lavandula or Rosmarinus can be proposed as a potential add-on strategy in the treatment of neurodegenerative diseases through intranasal administration, due to the well-known beneficial effects of essential oils and the mucoadhesive properties of NLC.
A qPCR Assay for the Fast Detection and Quantification of Colletotrichum lupini
Authors: Kamber Tim , Malpica-López Nachelli , Messmer Monika M. , Oberhänsli Thomas , Arncken Christine , Alkemade Joris A. , Hohmann Pierre
Published: July 2021

White lupin (Lupinus albus) represents an important legume crop in Europe and other parts of the world due to its high protein content and potential for low-input agriculture. However, most cultivars are susceptible to anthracnose caused by Colletotrichum lupini, a seed- and air-borne fungal pathogen that causes severe yield losses. The aim of this work was to develop a C. lupini-specific quantitative real-time TaqMan PCR assay that allows for quick and reliable detection and quantification of the pathogen in infected seed and plant material. Quantification of C. lupini DNA in dry seeds allowed us to distinguish infected and certified (non-infected) seed batches with DNA loads corresponding to the disease score index and yield of the mother plants. Additionally, C. lupini DNA could be detected in infected lupin shoots and close to the infection site, thereby allowing us to study the disease cycle of this hemibiotrophic pathogen. This qPCR assay provides a useful diagnostic tool to determine anthracnose infection levels of white lupin seeds and will facilitate the use of seed health assessments as a strategy to reduce the primary infection source and spread of this disease.
A Comprehensive Study of the Antibacterial Activity of Bioactive Juice and Extracts from Pomegranate (Punica granatum L.) Peels and Seeds
Authors: Kupnik Kaja , Primožič Mateja , Vasić Katja , Knez Željko , Leitgeb Maja
Published: July 2021

Due to the growing awareness of Punica granatum fruit’s health-promoting properties, the pomegranate is increasingly used for food purposes. This results in the formation of biological waste products such as peels. A biowaste circular bioeconomy strategy holds great prospective for a sustainable economy. Therefore, a sustainable and environmentally friendly way of disposing of waste (e.g., use of biowaste to obtain high-value components (e.g., punicalagins, enzymes)) is crucial for the protection of the environment and human health. In the presented study, the content of total phenols and proanthocyanidins in ten samples of Punica granatum fruit (juice, aqueous (H2O) and ethanolic (EtOH) extracts of peels and seeds) was determined. Peel extracts were found to be the richest in the content of secondary metabolites and showed extremely high antioxidant potential (approximately 90% inhibition: DPPH radical scavenging activity). To the best of our knowledge, this is the first comparative study to determine the enzymatic activity of α-amylase, lipase, peroxidase, protease, and transglutaminase in different P. granatum samples. Furthermore, the antibacterial efficacy of all P. granatum samples was qualitatively determined against three strains of Gram-negative (Escherichia coli, Pseudomonas aeruginosa, and Pseudomonas fluorescens) and three strains of Gram-positive (Bacillus cereus, Staphylococcus aureus, and Streptococcus pyogenes) bacteria, susceptible to gaining antibiotic resistance. Moreover, the most promising peel extracts were quantified for antibacterial efficacy against tested bacteria at five different concentrations. All samples slowed down and inhibited the growth of all tested bacteria. MIC90 values (2.7 or 0.3 mg/mL) were determined in 18 out of 24 experiments (four samples, six bacteria tested). There is no research in the reviewed literature that is current with such detailed and comprehensive determination of P. granatum peel extracts antibacterial activity. The results of the research showed great potential for the use of P. granatum in the field of antibacterial activity in biomedicine applications and in the cosmetic, food, and pharmaceutical industries.
Effect of Relative Humidity on the Electrospinning Performance of Regenerated Silk Solution
Authors: Park Bo Kyung , Um In Chul
Published: July 2021

Recently, the electrospun silk web has been intensively studied in terms of its biomedical applications, including tissue engineering scaffolds, due to its good biocompatibility, cytocompatibility, and biodegradability. In this study, the effect of relative humidity (RH) conditions on the morphology of electrospun silk fiber and the electrospinning production rate of silk solution was examined. In addition, the effect of RH on the molecular conformation of electrospun silk web was examined using Fourier transform infrared (FTIR) spectroscopy. As RH was increased, the maximum electrospinning rate of silk solution and fiber diameter of the resultant electrospun silk web were decreased. When RH was increased to 60%, some beads were observed, which showed that the electrospinnability of silk formic acid solution deteriorated with an increase in RH. The FTIR results showed that electrospun silk web was partially β-sheet crystallized and RH did not affect the molecular conformation of silk.
A Multifaceted Approach for Cryogenic Waste Tire Recycling
Authors: Yerezhep Darkhan , Tychengulova Aliya , Sokolov Dmitriy , Aldiyarov Abdurakhman
Published: July 2021

One of the important aspects for degradation of the life quality is the ever increasing volume and range of industrial wastes. Polymer wastes, such as automotive tire rubber, are a source of long-term environmental pollution. This paper presents an approach to simplifying the rubber waste recycling process using cryogenic temperatures. The temperature of cryogenic treatment is ranged from 77 K to 280 K. Liquid nitrogen was used as a cryoagent for laboratory tests. Experimental and numerical studies have been carried out to determine the optimal conditions for the recycling process. Numerical studies were performed using the COMSOL Multiphysics cross-platform software. The optimal force of mechanical shock for the destruction of a tire which turned into a glassy state after cryoexposure was determined experimentally. The chemical and physical properties of the final product (crumb rubber) have been studied by scanning electron microscopy and energy dispersive X-ray spectroscopy. The analysis shows that the morphology and elemental composition of the samples remain practically unchanged, demonstrating environmental friendliness of the proposed process.
Rapid, Sensitive, and Sustainable Reversed-Phase HPTLC Method in Comparison to the Normal-Phase HPTLC for the Determination of Pterostilbene in Capsule Dosage Form
Authors: Alam Prawez , Shakeel Faiyaz , Alqarni Mohammed H. , Foudah Ahmed I. , Faiyazuddin Md. , Alshehri Sultan
Published: July 2021

The greenness evaluation of literature analytical methods for pterostilbene (PT) analysis was not performed. Accordingly, the rapid, sensitive, and green/sustainable reversed-phase high-performance thin-layer chromatography (RP-HPTLC) method was developed and compared to the normal-phase (NP)-HPTLC (NP-HPTLC) for the estimation of PT with a classical univariate calibration. The RP quantification of PT was performed using green solvent systems; however, the NP analysis of PT was performed using routine solvent systems. The PT was detected at 302 nm for both of the methods. The greenness scores for the current analytical assays were evaluated by the analytical GREEnness (AGREE) metric approach. The classical univariate calibration for RP and NP methods indicated the linearity range as 10–1600 and 30–400 ng band−1, respectively. The RP method was more reliable for PT analysis compared to the NP method. The PT contents in commercial capsule dosage form were found to be 100.84% using the RP method; however, the PT contents in commercial capsule dosage form were determined as 92.59% using the NP method. The AGREE scores for RP and NP methods were 0.78 and 0.46, respectively. The sustainable RP-HPTLC assay was able to detect PT in the presence of its degradation products, and hence it can be considered as a selective and stability-indicating method. Accordingly, the RP-HPTLC method with univariate calibration has been considered as a superior method over the NP-HPTLC method for PT analysis.
The Covenant Renewal Ceremony as the Main Function of Qumran
Authors: Vainstub Daniel
Published: July 2021

Unlike any other group or philosophy in ancient Judaism, the yaḥad sect obliged all members of the sect to leave their places of residence all over the country and gather in the sect’s central site to participate in a special annual ceremony of renewal of the covenant between God and each of the members. The increase of the communities that composed the sect and their spread over the entire country during the first century BCE required the development of the appropriate infrastructure for hosting this annual gathering at Qumran. Consequently, the hosting of the gathering became the main function of the site, and the southern esplanade with the buildings surrounding it became the epicenter of the site.
The Making of Nordic Monasticism, c. 1076–c. 1350
Authors: Clark James G.
Published: July 2021

The introduction of regular religious life in the Nordic region is less well-documented than in the neighbouring kingdoms of northern Europe. In the absence of well-preserved manuscript and material remains, unfounded and sometimes distorting suppositions have been made about the timeline of monastic settlement and the character of the conventual life it brought. Recent archival and archaeological research can offer fresh insights into these questions. The arrival of authentic regular life may have been as early as the second quarter of the eleventh century in Denmark and Iceland, but there was no secure or stable community in any part of Scandinavia until the turn of the next century. A settled monastic network arose from a compact between the leadership of the secular church and the ruling elite, a partnership motivated as much by the shared pursuit of political, social and economic power as by any personal piety. Yet, the force of this patronal programme did not inhibit the development of monastic cultures reflected in books, original writings, church and conventual buildings, which bear comparison with the European mainstream.
Detecting Infected Cucumber Plants with Close-Range Multispectral Imagery
Authors: Fernández Claudio I. , Leblon Brigitte , Wang Jinfei , Haddadi Ata , Wang Keri
Published: July 2021

This study used close-range multispectral imagery over cucumber plants inside a commercial greenhouse to detect powdery mildew due to Podosphaera xanthii. It was collected using a MicaSense® RedEdge camera at 1.5 m over the top of the plant. Image registration was performed using Speeded-Up Robust Features (SURF) with an affine geometric transformation. The image background was removed using a binary mask created with the aligned NIR band of each image, and the illumination was corrected using Cheng et al.’s algorithm. Different features were computed, including RGB, image reflectance values, and several vegetation indices. For each feature, a fine Gaussian Support Vector Machines algorithm was trained and validated to classify healthy and infected pixels. The data set to train and validate the SVM was composed of 1000 healthy and 1000 infected pixels, split 70–30% into training and validation datasets, respectively. The overall validation accuracy was 89, 73, 82, 51, and 48%, respectively, for blue, green, red, red-edge, and NIR band image. With the RGB images, we obtained an overall validation accuracy of 89%, while the best vegetation index image was the PMVI-2 image which produced an overall accuracy of 81%. Using the five bands together, overall accuracy dropped from 99% in the training to 57% in the validation dataset. While the results of this work are promising, further research should be considered to increase the number of images to achieve better training and validation datasets.
The Impact of Phenological Developments on Interferometric and Polarimetric Crop Signatures Derived from Sentinel-1: Examples from the DEMMIN Study Site (Germany)
Authors: Löw Johannes , Ullmann Tobias , Conrad Christopher
Published: July 2021

This study explores the potential of Sentinel-1 Synthetic Aperture Radar (SAR) to identify phenological phases of wheat, sugar beet, and canola. Breakpoint and extreme value analyses were applied to a dense time series of interferometric (InSAR) and polarimetric (PolSAR) features recorded during the growing season of 2017 at the JECAM site DEMMIN (Germany). The analyses of breakpoints and extrema allowed for the distinction of vegetative and reproductive stages for wheat and canola. Certain phenological stages, measured in situ using the BBCH-scale, such as leaf development and rosette growth of sugar beet or stem elongation and ripening of wheat, were detectable by a combination of InSAR coherence, polarimetric Alpha and Entropy, and backscatter (VV/VH). Except for some fringe cases, the temporal difference between in situ observations and breakpoints or extrema ranged from zero to five days. Backscatter produced the signature that generated the most breakpoints and extrema. However, certain micro stadia, such as leaf development of BBCH 10 of sugar beet or flowering BBCH 69 of wheat, were only identifiable by the InSAR coherence and Alpha. Hence, it is concluded that combining PolSAR and InSAR features increases the number of detectable phenological events in the phenological cycles of crops.
Prospects for Long-Term Agriculture in Southern Africa: Emergent Dynamics of Savannah Ecosystems from Remote Sensing Observations
Authors: Wei Tiffany M. , Barros Ana P.
Published: July 2021

Hydro-climatic resilience is an essential element of food security. The miombo ecosystem in Southern Africa supports varied land uses for a growing population. Albedo, Leaf Area Index (LAI), Fractional Vegetation Cover (FVC), Solar-Induced chlorophyll Fluorescence (SIF), and precipitation remote-sensing data for current climate were jointly analyzed to explore vegetation dynamics and water availability feedbacks. Changes in the surface energy balance tied to vegetation status were examined in the light of an hourly albedo product with improved atmospheric correction derived for this study. Phase-space analysis shows that the albedo’s seasonality tracks the landscape-scale functional stability of miombo and woody savanna with respect to precipitation variations. Miombo exhibits the best adaptive traits to water stress which highlights synergies among root-system water uptake capacity, vegetation architecture, and landscape hydro-geomorphology. This explains why efforts to conserve the spatial structure of the miombo forest in sustainable farming of seasonal wetlands have led to significant crop yield increases. Grass savanna’s high vulnerability to water stress is illustrative of potential run-away impacts of miombo deforestation. This study suggests that phase-space analysis of albedo, SIF, and FVC can be used as operational diagnostics of ecosystem health.
Estimation of Paddy Rice Nitrogen Content and Accumulation Both at Leaf and Plant Levels from UAV Hyperspectral Imagery
Authors: Wang Li , Chen Shuisen , Li Dan , Wang Chongyang , Jiang Hao , Zheng Qiong , Peng Zhiping
Published: July 2021

Remote sensing-based mapping of crop nitrogen (N) status is beneficial for precision N management over large geographic regions. Both leaf/canopy level nitrogen content and accumulation are valuable for crop nutrient diagnosis. However, previous studies mainly focused on leaf nitrogen content (LNC) estimation. The effects of growth stages on the modeling accuracy have not been widely discussed. This study aimed to estimate different paddy rice N traits—LNC, plant nitrogen content (PNC), leaf nitrogen accumulation (LNA) and plant nitrogen accumulation (PNA)—from unmanned aerial vehicle (UAV)-based hyperspectral images. Additionally, the effects of the growth stage were evaluated. Univariate regression models on vegetation indices (VIs), the traditional multivariate calibration method, partial least squares regression (PLSR) and modern machine learning (ML) methods, including artificial neural network (ANN), random forest (RF), and support vector machine (SVM), were evaluated both over the whole growing season and in each single growth stage (including the tillering, jointing, booting and heading growth stages). The results indicate that the correlation between the four nitrogen traits and the other three biochemical traits—leaf chlorophyll content, canopy chlorophyll content and aboveground biomass—are affected by the growth stage. Within a single growth stage, the performance of selected VIs is relatively constant. For the full-growth-stage models, the performance of the VI-based models is more diverse. For the full-growth-stage models, the transformed chlorophyll absorption in the reflectance index/optimized soil-adjusted vegetation index (TCARI/OSAVI) performs best for LNC, PNC and PNA estimation, while the three band vegetation index (TBVITian) performs best for LNA estimation. There are no obvious patterns regarding which method performs the best of the PLSR, ANN, RF and SVM in either the growth-stage-specific or full-growth-stage models. For the growth-stage-specific models, a lower mean relative error (MRE) and higher R2 can be acquired at the tillering and jointing growth stages. The PLSR and ML methods yield obviously better estimation accuracy for the full-growth-stage models than the VI-based models. For the growth-stage-specific models, the performance of VI-based models seems optimal and cannot be obviously surpassed. These results suggest that building linear regression models on VIs for paddy rice nitrogen traits estimation is still a reasonable choice when only a single growth stage is involved. However, when multiple growth stages are involved or missing the phenology information, using PLSR or ML methods is a better option.
Preliminary Investigation on Phytoplankton Dynamics and Primary Production Models in an Oligotrophic Lake from Remote Sensing Measurements
Authors: Cesana Ilaria , Bresciani Mariano , Cogliati Sergio , Giardino Claudia , Gupana Remika , Manca Dario , Santabarbara Stefano , Pinardi Monica , Austoni Martina , Lami Andrea , Colombo Roberto
Published: July 2021

The aim of this study is to test a series of methods relying on hyperspectral measurements to characterize phytoplankton in clear lake waters. The phytoplankton temporal evolutions were analyzed exploiting remote sensed indices and metrics linked to the amount of light reaching the target (EPAR), the chlorophyll-a concentration ([Chl-a]OC4) and the fluorescence emission proxy. The latter one evaluated by an adapted version of the Fluorescence Line Height algorithm (FFLH). A peculiar trend was observed around the solar noon during the clear sky days. It is characterized by a drop of the FFLH metric and the [Chl-a]OC4 index. In addition to remote sensed parameters, water samples were also collected and analyzed to characterize the water body and to evaluate the in-situ fluorescence (FF) and absorbed light (FA). The relations between the remote sensed quantities and the in-situ values were employed to develop and test several phytoplankton primary production (PP) models. Promising results were achieved replacing the FA by the EPAR or FFLH in the equation evaluating a PP proxy (R2 > 0.65). This study represents a preliminary outcome supporting the PP monitoring in inland waters by means of remote sensing-based indices and fluorescence metrics.
Analytical Model of Induction Machines with Multiple Cage Faults Using the Winding Tensor Approach
Authors: Martinez-Roman Javier , Puche-Panadero Ruben , Sapena-Bano Angel , Terron-Santiago Carla , Burriel-Valencia Jordi , Pineda-Sanchez Manuel
Published: July 2021

Induction machines (IMs) are one of the main sources of mechanical power in many industrial processes, especially squirrel cage IMs (SCIMs), due to their robustness and reliability. Their sudden stoppage due to undetected faults may cause costly production breakdowns. One of the most frequent types of faults are cage faults (bar and end ring segment breakages), especially in motors that directly drive high-inertia loads (such as fans), in motors with frequent starts and stops, and in case of poorly manufactured cage windings. A continuous monitoring of IMs is needed to reduce this risk, integrated in plant-wide condition based maintenance (CBM) systems. Diverse diagnostic techniques have been proposed in the technical literature, either data-based, detecting fault-characteristic perturbations in the data collected from the IM, and model-based, observing the differences between the data collected from the actual IM and from its digital twin model. In both cases, fast and accurate IM models are needed to develop and optimize the fault diagnosis techniques. On the one hand, the finite elements approach can provide highly accurate models, but its computational cost and processing requirements are very high to be used in on-line fault diagnostic systems. On the other hand, analytical models can be much faster, but they can be very complex in case of highly asymmetrical machines, such as IMs with multiple cage faults. In this work, a new method is proposed for the analytical modelling of IMs with asymmetrical cage windings using a tensor based approach, which greatly reduces this complexity by applying routine tensor algebra to obtain the parameters of the faulty IM model from the healthy one. This winding tensor approach is explained theoretically and validated with the diagnosis of a commercial IM with multiple cage faults.
Convolver Design and Convolve-Accumulate Unit Design for Low-Power Edge Computing
Authors: Kao Hsu-Yu , Chen Xin-Jia , Huang Shih-Hsu
Published: July 2021

Convolution operations have a significant influence on the overall performance of a convolutional neural network, especially in edge-computing hardware design. In this paper, we propose a low-power signed convolver hardware architecture that is well suited for low-power edge computing. The basic idea of the proposed convolver design is to combine all multipliers’ final additions and their corresponding adder tree to form a partial product matrix (PPM) and then to use the reduction tree algorithm to reduce this PPM. As a result, compared with the state-of-the-art approach, our convolver design not only saves a lot of carry propagation adders but also saves one clock cycle per convolution operation. Moreover, the proposed convolver design can be adapted for different dataflows (including input stationary dataflow, weight stationary dataflow, and output stationary dataflow). According to dataflows, two types of convolve-accumulate units are proposed to perform the accumulation of convolution results. The results show that, compared with the state-of-the-art approach, the proposed convolver design can save 15.6% power consumption. Furthermore, compared with the state-of-the-art approach, on average, the proposed convolve-accumulate units can reduce 15.7% power consumption.
Wearable Edge AI Applications for Ecological Environments
Authors: Silva Mateus C. , da Silva Jonathan C. F. , Delabrida Saul , Bianchi Andrea G. C. , Ribeiro Sérvio P. , Silva Jorge Sá , Oliveira Ricardo A. R.
Published: July 2021

Ecological environments research helps to assess the impacts on forests and managing forests. The usage of novel software and hardware technologies enforces the solution of tasks related to this problem. In addition, the lack of connectivity for large data throughput raises the demand for edge-computing-based solutions towards this goal. Therefore, in this work, we evaluate the opportunity of using a Wearable edge AI concept in a forest environment. For this matter, we propose a new approach to the hardware/software co-design process. We also address the possibility of creating wearable edge AI, where the wireless personal and body area networks are platforms for building applications using edge AI. Finally, we evaluate a case study to test the possibility of performing an edge AI task in a wearable-based environment. Thus, in this work, we evaluate the system to achieve the desired task, the hardware resource and performance, and the network latency associated with each part of the process. Through this work, we validated both the design pattern review and case study. In the case study, the developed algorithms could classify diseased leaves with a circa 90% accuracy with the proposed technique in the field. This results can be reviewed in the laboratory with more modern models that reached up to 96% global accuracy. The system could also perform the desired tasks with a quality factor of 0.95, considering the usage of three devices. Finally, it detected a disease epicenter with an offset of circa 0.5 m in a 6 m × 6 m × 12 m space. These results enforce the usage of the proposed methods in the targeted environment and the proposed changes in the co-design pattern.
Virtual Reality-Based Framework to Simulate Control Algorithms for Robotic Assistance and Rehabilitation Tasks through a Standing Wheelchair
Authors: Ortiz Jessica S. , Palacios-Navarro Guillermo , Andaluz Víctor H. , Guevara Bryan S.
Published: July 2021

The implementation of control algorithms oriented to robotic assistance and rehabilitation tasks for people with motor disabilities has been of increasing interest in recent years. However, practical implementation cannot be carried out unless one has the real robotic system availability. To overcome this drawback, this article presents the development of an interactive virtual reality (VR)-based framework that allows one to simulate the execution of rehabilitation tasks and robotic assistance through a robotic standing wheelchair. The virtual environment developed considers the kinematic and dynamic model of the standing human–wheelchair system with a displaced center of mass, since it can be displaced for different reasons, e.g.,: bad posture, limb amputations, obesity, etc. The standing wheelchair autonomous control scheme has been implemented through the Full Simulation (FS) and Hardware in the Loop (HIL) techniques. Finally, the performance of the virtual control schemes has been shown by means of several experiments based on robotic assistance and rehabilitation for people with motor disabilities.
Estimation of Earthquake Early Warning Parameters for Eastern Gulf of Corinth and Western Attica Region (Greece). First Results
Authors: Vallianatos Filippos , Karakonstantis Andreas , Sakelariou Nikolaos
Published: July 2021

The main goal of an Earthquake Early Warning System (EEWS) is to alert before the arrival of damaging waves using the first seismic arrival as a proxy, thus becoming an important operational tool for real-time seismic risk management on a short timescale. EEWSs are based on the use of scaling relations between parameters measured on the initial portion of the seismic signal after the arrival of the first wave. To explore the plausibility of EEWSs around the Eastern Gulf of Corinth and Western Attica, amplitude and frequency-based parameters, such as peak displacement (Pd), the integral of squared velocity (IV 2) and the characteristic period (τc), were analyzed. All parameters were estimated directly from the initial 3 s, 4 s, and 5 s signal windows (tw) after the P arrival. While further study is required on the behavior of the proxy quantities, we propose that the IV 2 parameter and the peak amplitudes of the first seconds of the P waves present significant stability and introduce the possibility of a future on-site EEWS for areas affected by earthquakes located in the Eastern Gulf of Corinth and Western Attica. Parameters related to regional-based EEWS need to be further evaluated.
Comparative Experimental Investigation on Optimal Parametric Array Types
Authors: Jung Donghwan , Song Jiyoung , Kim Jeasoo , Lee Jaehyuk
Published: July 2021

As a sound transmitting device that relies on the nonlinearity of a medium, a parametric array (PA) can generate high-directivity low-frequency signals using a small aperture transducer and high-frequency signals. Despite their relatively low source level, the PA is frequently used to measure the acoustic properties of materials in low-frequency regions owing to their high directivity in confined acoustic water tanks. Therefore, methods for improving the source level of secondary signals are of interest. Currently, there are two driving methods for PA: the dual-frequency PA and the broadband PA with amplitude modulation. In this study, we share the results of an elaborate and comparative experimental investigation of these two driving methods. Comparisons are made and discussed in terms of the intensity of the generated secondary signal and its characteristics in the frequency domain. Based on these factors, we confirmed that the broadband PA was more suitable as the sound source of the low-frequency characteristic measurement system of acoustic materials.
Comparison of Aerial Thermal Infrared Imagery and Helicopter Surveys of Bison (Bison bison) in Grand Canyon National Park, USA
Authors: Hennig Jacob D. , Schoenecker Kathryn A. , Terwilliger Miranda L.N. , Holm Gregory W. , Laake Jeffrey L.
Published: July 2021

Aerial thermal infrared (TIR) surveys are an attractive option for estimating abundances of large mammals inhabiting extensive and heterogeneous terrain. Compared to standard helicopter or fixed-wing aerial surveys, TIR flights can be conducted at higher altitudes translating into greater spatial coverage and increased observer safety; however, monetary costs are much greater. Further, there is no consensus on whether TIR surveys offer improved detection. Consequently, we performed a study to compare results of a TIR and helicopter survey of bison (Bison bison) on the Powell Plateau in Grand Canyon National Park, USA. We also compared results of both surveys to estimates obtained using a larger dataset of bison helicopter detections along the entire North Rim of the Grand Canyon. Observers in the TIR survey counted fewer individual bison than helicopter observers (101 to 127) and the TIR survey cost was 367% higher. Additionally, the TIR estimate was 18.8% lower than the estimate obtained using a larger dataset, while the comparative helicopter survey was 9.3% lower. Despite our small sample size, we found that helicopter surveys are currently the best method for estimating bison abundances in dense canopy cover sites due to ostensibly more accurate estimates and lower cost compared to TIR surveys. Additional research will be needed to evaluate the efficacy of these methods, as well as very high resolution satellite imagery, for bison populations in more open landscapes.
Water Content Monitoring in Water-in-Crude-Oil Emulsions Using an Ultrasonic Multiple-Backscattering Sensor
Authors: Durán Alberto L. , Franco Ediguer E. , Reyna Carlos A. B. , Pérez Nicolás , Tsuzuki Marcos S. G. , Buiochi Flávio
Published: July 2021

This work shows the application of an ultrasonic multiple-scattering sensor for monitoring water-in-petroleum emulsions. The sensor consists of a commercial ultrasonic transducer with an array of cylindrical scatterers placed in the near field. The scatterers are thin metal bars arranged in rows in front of the transducer. The backscattering signals were analyzed by calculating the wave energy and by a cross-correlation between signal segments; they were also used to determine the propagation velocity in the emulsions. The tests performed used emulsions with water volume concentrations from 0% to 50%. The results showed that both the signal energy and propagation velocity strongly depended on the concentration of water in the emulsion. Therefore, the ultrasonic multiple-scattering sensor can be used for on-line and real-time monitoring of the water content in water-in-crude-oil emulsions.
EEG-Based Emotion Recognition by Convolutional Neural Network with Multi-Scale Kernels
Authors: Phan Tran-Dac-Thinh , Kim Soo-Hyung , Yang Hyung-Jeong , Lee Guee-Sang
Published: July 2021

Besides facial or gesture-based emotion recognition, Electroencephalogram (EEG) data have been drawing attention thanks to their capability in countering the effect of deceptive external expressions of humans, like faces or speeches. Emotion recognition based on EEG signals heavily relies on the features and their delineation, which requires the selection of feature categories converted from the raw signals and types of expressions that could display the intrinsic properties of an individual signal or a group of them. Moreover, the correlation or interaction among channels and frequency bands also contain crucial information for emotional state prediction, and it is commonly disregarded in conventional approaches. Therefore, in our method, the correlation between 32 channels and frequency bands were put into use to enhance the emotion prediction performance. The extracted features chosen from the time domain were arranged into feature-homogeneous matrices, with their positions following the corresponding electrodes placed on the scalp. Based on this 3D representation of EEG signals, the model must have the ability to learn the local and global patterns that describe the short and long-range relations of EEG channels, along with the embedded features. To deal with this problem, we proposed the 2D CNN with different kernel-size of convolutional layers assembled into a convolution block, combining features that were distributed in small and large regions. Ten-fold cross validation was conducted on the DEAP dataset to prove the effectiveness of our approach. We achieved the average accuracies of 98.27% and 98.36% for arousal and valence binary classification, respectively.
Analysis of the Safety Resilience Implementation in the Maritime Industry at Public and Private Companies (A Case Study in Indonesia)
Authors: Djunaidi Zulkifli , Tantia Annisa Ayu , Wirawan Mufti
Published: July 2021

(1) Background: The resilience concept shows performance improvement in four potential aspects consisting of the ability to respond, provide anticipatory action, control things that occur internally and externally, as well as the learning process of what is going right and what is going wrong. This study aims to analyze the safety resilience implementation in the Indonesian maritime sector. (2) Method: This is a descriptive study using semi-quantitative methods, using interview guides based on the Resilience Assessment Grid (RAG). The sampling technique is purposive sampling. (3) Results: The level of implementation of safety resilience at the public company was 75.1%, while the private company was 70.2%. The score for each safety resilience element in the public and private companies are as follows: the ability to respond (80%), learning ability (74.62%), monitoring ability (70.77%), and the ability to anticipate (66.92%). (4) Conclusion: The safety resilience implementation in Indonesian sea transportation shipping has not been optimal in implementing the safety resilience concept. The focus of implementing safety is still on preventing and controlling accidents. The other orientation of ability improvement in the safety resilience concept has not been implemented.
Constitutional Values in the Gig-Economy? Why Labor Law Fails at Platform Work, and What Can We Do about It?
Authors: Ződi Zsolt , Török Bernát
Published: July 2021

Gig-work, or platform work, has been in the crosshairs of regulators since roughly the mid-2010s. The employment of an increasing number of platform workers raises a number of problems, however, there is no longer a consensus as to whether these problems are only the emergence of certain well-established labor law issues in a new guise, or completely new ones. To date, only one possible solution seems to have emerged, that of bringing platform work under the umbrella of labor law. This study argues, on the one hand, that platform work has a characteristic that was previously unknown in the world of labor relations (algorithmic and data-based work organization) and, on the other hand, that it has two other characteristics (tripartite structure and network effect) that create an entirely new quality that requires innovative legal approaches. The study selects some of the recent European Union standards regulating various kinds of online platforms which may also provide useful solutions for the regulation of platform work.
The Value of Critical Thinking in Higher Education and the Labour Market: The Voice of Stakeholders
Authors: Indrašienė Valdonė , Jegelevičienė Violeta , Merfeldaitė Odeta , Penkauskienė Daiva , Pivorienė Jolanta , Railienė Asta , Sadauskas Justinas , Valavičienė Natalija
Published: July 2021

Critical thinking has been more than just a part of academic rhetoric and educational practice for some time now. In the rapidly changing world of information flow, critical thinking is often identified as the goal of higher education, and in the modern labour market, the importance of critical thinking to an organisation’s success is emphasised. Critical thinking is recognised as one of the tools for the formation and development of human and social capital. Nevertheless, there is a lack of evidence about the manifestation in the labour market of the critical thinking developed at institutions of higher education. This article seeks to reveal the attitude toward the importance of critical thinking in the modern labour market and toward the responsibility for developing it from the perspective of different stakeholder groups (lecturers, students, employers and employees) (the case of Lithuania). Quantitative research methodology was chosen, using a questionnaire for data collection. It was found that in both higher education and the labour market, critical thinking is treated as a developed and dynamic competence that encompasses both cognitive skills and dispositions. All of the stakeholder groups consider inference and argumentation to be the most important critical thinking skills in the modern labour market. Critical thinking dispositions such as self-confidence and fairness are the most valued. All of the stakeholder groups delegate responsibility for the development of critical thinking to the individual. In evaluating critical thinking, no divide was established between the higher education and labour market segments. The most differences in attitudes emerged in evaluating the assumption of responsibility for the development of critical thinking.
Influence of Natural Aggregate Crushing Process on Crushing Strength Index
Authors: Pacana Andrzej , Siwiec Dominika , Bednarova Lucia , Sofranko Marian , Vegsoova Olga , Cvoliga Martin
Published: July 2021

Crushing is one of the most energy-consuming technological processes. The purpose of grinding is to achieve the desired grain size of mineral raw materials. The process of grinding consists of many factors, for example, the size and form of crushed grains, as well as their mutual arrangement inside the crushing machine chamber, the technological parameters of the crusher, the material properties, and the speed of the moving grains. One of the key parameters of the aggregate is its resistance to grinding. Resistance to grinding is related to the strength of the products made from aggregates subjected to grinding, which affects the overall quality of these products. Therefore, the aim of this study is to analyze the impact of the crushing of natural aggregate on the LA crumbling strength index. Two types of aggregates were analyzed—natural gravel and natural pebbles crushed in a crusher. Aggregates were acquired from two mines belonging to the plant Kruszgeo S.A. in Rzeszów, i.e., ZEK (Zakład Eksploatacji Kruszywa) Ostrów and ZEK Strzegocice II. The aggregate crushing process was carried out for 4–8 mm and 10–14 mm fractions using cone crushers of the 1044 type. Aggregate crushing was carried out in a Los Angeles drum, in accordance with the requirements of EN 1097-2:2020. The analysis showed that for grits of the 10–14 mm fraction, the lower values of the LA indices were obtained, which allows for obtaining a bigger index of crushing strength than in the case of crushing using the 4–8 mm fraction. This analysis showed how important the process of grinding aggregates is and, thus, the appropriate selection of fractions for the grit crushing process for the aggregate strength on grinding. Subjecting the aggregate to the grinding process results in an improvement in the crushing strength indicator, thus obtaining better strength parameters of the products manufactured from the aggregates subjected to the process of crushing (for example, concrete). The originality of the study is an analysis of key Polish aggregates and the crushing strength index.
Seed-Propagated Summer Apples: Great Morphological and Biochemical Diversity
Authors: Karatas Neva , Ercisli Sezai , Bozhuyuk Mehmet Ramazan , Cakir Ozlem , Necas Tomas , Ondrasek Ivo
Published: July 2021

The northeastern Anatolia region of Turkey is one of the richest plant biodiversity areas in Turkey. This study describes some important tree and fruit characteristics of 20 seed-propagated summer apple genotypes from northeastern Anatolia using morphological and biochemical markers. The genotypes were evaluated morphologically for tree growth habit, ripening date, fruit weight, fruit firmness, fruit shape, fruit color, fruit taste, juiciness and aroma. The biochemical characteristics measured were organic acids, SSC (soluble solid content), titratable acidity, vitamin C, total phenolic content and antioxidant capacity. We found significant differences for most of the morphological and biochemical characteristics. The genotypes exhibited quite diverse harvest dates ranging from 4 July to 16 August. Summer apple genotypes had fruit weight between 101.9 g and 133.5 g. The genotypes had diverse fruit shapes, including round, conic and oblate, and over fruit colours such as pink, red, yellow and green. Genotypes GUM7 and GUM13 stood out for fruit weight, SSC, total phenolic and antioxidant capacity. GUM7 and GUM13 present dissimilarity from the other genotypes. While the first showed a lower average fruit weight, SSC, total phenolic content and antioxidant capacity, the second revealed higher average of fruit weight, total phenolic content, antioxidant capacity and higher SSC. Due to their favorable characteristics, GUM13 can be used for further crosses with genotypes of other groups, which also present favorable characteristics.
Neuroeconomic Decisions in Cocoa Producers: Impact of Cooperative Innovation Methodology on Prospecting for Fair Trade Organic Niche as an Incentive for Agricultural Sustainability
Authors: Zúniga Aguilar Isaac
Published: July 2021

This article focuses on analyzing the neuroeconomic decisions in cocoa producers and the impact of this methodology on the productivity of fair trade organic cocoa producers on the population of Nuevo Bambamarca, province of Tocache, Peru. The main elements of the methodology are the incentive phase of associativity, the alignment phase to macro trends, the prospecting phase of the country to be exported to, the prospecting phase of the type of niche market, the prospecting phase of fair participation, the innovation and design phase of the prototype, the standardization phase of the raw material technical specifications for collection, the strengthening phase the producer’s commitment, the learning phase of the producer in crop management, and the evaluation phase of productivity in the field. This research study is pre-experimental, cross-sectional, explanatory, and descriptive. The experimental group made up of 20 fair trade organic cocoa producers of the Cooperativa Agroindustrial Naranjillo obtained on average a profitability of 143 EUR per campaign higher than the control group made up of 20 producers of conventional cocoa that did not belong to the cooperative who obtained a loss of −642 EUR per campaign, even with the same purchase price of 1.92 EUR per kg for both cases during the 2011 campaign. It is concluded that Hypothesis 1 is met, it shows that the cooperative innovation methodology of prospecting for fair trade organic niche encourages the productivity of producers of the experimental group with respect to the control group.
Do Attention and Memory Tasks Require the Same Lighting? A Study in University Classrooms
Authors: Llinares Carmen , Castilla Nuria , Higuera-Trujillo Juan Luis
Published: July 2021

Lighting plays a fundamental role in learning spaces as it influences students’ performance. Nowadays, new technologies and new teaching methods in higher education mean that very different visual tasks are performed in the classroom, so further research is necessary to identify what lighting is best suited to these new tasks. The objective of the study is to analyse the impact that variations in levels of illuminance and Correlated Colour Temperature (CCT) of classrooms have on the cognitive functions (attention and memory) of university students. The cognitive performance of 90 participants was evaluated based on attention and memory tasks. The participants had to view nine virtual classroom configurations, with three different illuminance settings (100 lx, 300 lx and 500 lx) and three CCTs (3000 K, 4000 K and 6500 K). The results showed that attention and memory tasks require different level of illumination. While attention improves with higher light levels, memory improves with lower light levels. Higher CCTs generate better performance in both attention and memory tasks. These results highlight the link between lighting and students’ cognitive responses. This study and its methodology can be useful for architects and researchers as they establish lighting design guidelines capable of improving students’ cognitive processes.