bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Plasma Activated Water on Maize (Zea mays L.) under Arsenic Stress
Authors: Lukacova Zuzana , Svubova Renata , Selvekova Patricia , Hensel Karol
Published: September 2021

Plasma activated water (PAW) is a source of various chemical species useful for plant growth, development, and stress response. In the present study, PAW was generated by a transient spark discharge (TS) operated in ambient air and used on maize corns and seedlings in the 3 day paper rolls cultivation followed by 10 day hydroponics cultivation. For 3 day cultivation, two pre-treatments were established, “priming PAW” and “rolls PAW”, with corns imbibed for 6 h in the PAW and then watered daily by fresh water and PAW, respectively. The roots and the shoot were then analyzed for guaiacol peroxidase (G-POX, POX) activity, root tissues for their lignification, and root cell walls for in situ POX activity. To evaluate the potential of PAW in the alleviation abiotic stress, ten randomly selected seedlings were hydroponically cultivated for the following 10 days in 0.5 Hoagland nutrient solutions with and without 150 μM As. The seedlings were then analyzed for POX and catalase (CAT) activities after As treatment, their leaves for photosynthetic pigments concentration, and leaves and roots for As concentration. The PAW improved the growth of the 3 day-old seedlings in terms of the root and the shoot length, while roots revealed accelerated endodermal development. After the following 10 day cultivation, roots from PAW pre-treatment were shorter and thinner but more branched than the control roots. The PAW also enhanced the POX activity immediately after the imbibition and in the 3 day old roots. After 10 day hydroponic cultivation, antioxidant response depended on the PAW pre-treatment. CAT activity was higher in As treatments compared to the corresponding PAW treatments, while POX activity was not obvious, and its elevated activity was found only in the priming PAW treatment. The PAW pre-treatment protected chlorophylls in the following treatments combined with As, while carotenoids increased in treatments despite PAW pre-treatment. Finally, the accumulation of As in the roots was not affected by PAW pre-treatment but increased in the leaves.
LDPE/Bismuth Oxide Nanocomposite: Preparation, Characterization and Application in X-ray Shielding
Authors: Alshahri Saad , Alsuhybani Mohammed , Alosime Eid , Almurayshid Mansour , Alrwais Alhanouf , Alotaibi Salha
Published: September 2021

Recently developed polymer-based composites could prove useful in many applications such as in radiation shielding. In this work, the potential of a bismuth oxide (Bi2O3) nanofiller based on an LDPE polymer was developed as lead-free X-ray radiation shielding offering the benefits of lightness, low-cost and non-toxic compared to pure lead. Three different LDPE-based composites were prepared with varying weight percentages of Bi2O3: 5%, 10% and 15%. The characterizations were extended to include structural properties, physical features, mechanical and thermal properties, and radiation shielding efficiency for the prepared nanocomposites. The results revealed that the incorporation of the Bi2O3 nanofiller into an LDPE improved the density of the composites. There was also a slight increase in the tensile strength and tensile modulus. In addition, there was a clear improvement in the efficiency of the shield when fillers were added to the LDPE polymer. The LDPE + Bi2O3 (15%) composite needed the lowest thickness to attenuate 50% of the incident X-rays. The LDPE + Bi2O3 (15%) polymer can also block around 80% of X-rays at 47.9 keV. In real practice, a thicker shield of the proposed composite materials, or a higher percentage of the filler could be employed to safely ensure the radiation is blocked.
Bladder Substitution: The Role of Tissue Engineering and Biomaterials
Authors: Casarin Martina , Morlacco Alessandro , Dal Moro Fabrizio
Published: September 2021

Tissue engineering could play a major role in the setting of urinary diversion. Several conditions cause the functional or anatomic loss of urinary bladder, requiring reconstructive procedures on the urinary tract. Three main approaches are possible: (i) incontinent cutaneous diversion, such as ureterocutaneostomy, colonic or ileal conduit, (ii) continent pouch created using different segments of the gastrointestinal system and a cutaneous stoma, and (iii) orthotopic urinary diversion with an intestinal segment with spherical configuration and anastomosis to the urethra (neobladder, orthotopic bladder substitution). However, urinary diversions are associated with numerous complications, such as mucus production, electrolyte imbalances and increased malignant transformation potential. In this context, tissue engineering would have the fundamental role of creating a suitable material for urinary diversion, avoiding the use of bowel segments, and reducing complications. Materials used for the purpose of urinary substitution are biological in case of acellular tissue matrices and naturally derived materials, or artificial in case of synthetic polymers. However, only limited success has been achieved so far. The aim of this review is to present the ideal properties of a urinary tissue engineered scaffold and to examine the results achieved so far. The most promising studies have been highlighted in order to guide the choice of scaffolds and cells type for further evolutions.
Effects of Geniposide and Geniposidic Acid on Fluoxetine-Induced Muscle Atrophy in C2C12 Cells
Authors: Huang Shang-Ming , Lin Shuan-Ying , Chen Ming-Kai , Peng Chiung-Chi , Hsieh Chiu-Lan
Published: September 2021

Fluoxetine, an antidepressant known as a selective 5-hydroxytryptamine reuptake inhibitor (SSRI), can cause side effects such as muscle atrophy with long-term use, but the mechanism is not fully understood. Geniposide (GPS) and geniposidic acid (GPSA), the main components of Gardenia jasminoides fruit, have been shown to have biological activity in disease prevention, but their role in preventing FXT-related side effects such as muscle atrophy remains unclear. The process of muscle atrophy is a complex physiological mechanism involving the balance of protein synthesis and catabolism. In this study, we hypothesized that FXT may suppress hypertrophy signaling and activate the atrophy mechanisms, resulting in proteolysis and reduced protein synthesis, while geniposide (GPS) and geniposide acid (GPSA) may be beneficial in improving muscle weakness caused by FXT. The C2C12 cell model was used to examine the expression of hypertrophy signaling (PI3K, Akt, and mTOR) and protein break signals (FOXO, MuRF-1, and MyHC). Our data indicated that FXT inhibited MyHC and promoted MuRF-1 protein expression by downregulating the signaling pathways of p-ERK1/2, p-Akt, p-mTOR, and p-FOXO, resulting in a decrease in differentiation and myotube formation in C2C12 muscle cells, which further resulted in muscle atrophy. However, GPS and GPSA can positively regulate the atrophy mechanism induced by FXT in muscle cells, thereby ameliorating the imbalance in muscle synthesis. In conclusion, GPS and GPSA have the potential to attenuate the muscle loss caused by long-term FXT administration, diseases, or the aging process.
Improvement of Carrot Accelerated Solvent Extraction Efficacy Using Experimental Design and Chemometric Techniques
Authors: Tumbas Šaponjac Vesna , Kovačević Strahinja , Šeregelj Vanja , Šovljanski Olja , Mandić Anamarija , Ćetković Gordana , Vulić Jelena , Podunavac-Kuzmanović Sanja , Čanadanović-Brunet Jasna
Published: September 2021

Human studies have demonstrated the multiple health benefits of fruits and vegetables. Due to its high fiber, mineral and antioxidant content, carrot is an ideal source for the development of nutraceuticals or functional ingredients. Current research assesses accelerated solvent extraction (ASE) traits which affect the antioxidant qualities of carrot extract using response surface methodology (RSM), hierarchical cluster analysis (HCA), and the sum of ranking differences (SRD). A mixture of organic solvents, acetone, and ethanol with or without the addition of 20% water was applied. The total carotenoid and polyphenol contents in extracts, as well as their scavenging activity and reducing power, were used as responses for the optimization of ASE extraction. RSM optimization, in the case of 20% water involvement, included 49% of acetone and 31% of ethanol (Opt1), while in the case of pure organic solvents, pure ethanol was the best choice (Opt2). The results of HCA clearly pointed out significant differences between the properties of extracts with or without water. SRD analysis confirmed ethanol to be optimal as well. RSM, HCA, and SRD analysis confirmed the same conclusion—water in the solvent mixture can significantly affect the extraction efficacy, and the optimal solvent for extracting antioxidants from carrot by ASE is pure ethanol.
Effect of Tip Clearance on Helico-Axial Flow Pump Performance at Off-Design Case
Authors: Kan Nengqi , Liu Zongku , Shi Guangtai , Liu Xiaobing
Published: September 2021

To reveal the effect of tip clearance on the flow behaviors and pressurization performance of a helico-axial flow pump, the standard k-ε turbulence model is employed to simulate the flow characteristics in the self-developed helico-axial flow pump. The pressure, streamlines and turbulent kinetic energy in a helico-axial flow pump are analyzed. Results show that the tip leakage flow (TLF) forms a tip-separation vortex (TSV) when it enters the tip clearance and forms a tip-leakage vortex (TLV) when it leaves the tip clearance. As the blade tip clearance increases, the TLV moves along the blade from the leading edge (LE) to trailing edge (TE). At the same time, the entrainment between the TLV and the main flow deteriorates the flow pattern in the pump and causes great hydraulic loss. In addition, the existence of tip clearance also increases the possibility of TLV cavitation and has a great effect on the pressurization performance of the helico-axial flow pump. The research results provide the theoretical basis for the structural optimization design of the helico-axial flow pump.
Research on Object Detection Model Based on Feature Network Optimization
Authors: Zhang Xiaoliang , Wu Kehe , Ma Qi , Chen Zuge
Published: September 2021

As the object detection dataset scale is smaller than the image recognition dataset ImageNet scale, transfer learning has become a basic training method for deep learning object detection models, which pre-trains the backbone network of the object detection model on an ImageNet dataset to extract features for detection tasks. However, the classification task of detection focuses on the salient region features of an object, while the location task of detection focuses on the edge features, so there is a certain deviation between the features extracted by a pretrained backbone network and those needed by a localization task. To solve this problem, a decoupled self-attention (DSA) module is proposed for one-stage object-detection models in this paper. A DSA includes two decoupled self-attention branches, so it can extract appropriate features for different tasks. It is located between the Feature Pyramid Networks (FPN) and head networks of subtasks, and used to independently extract global features for different tasks based on FPN-fused features. Although the DSA network module is simple, it can effectively improve the performance of object detection, and can easily be embedded in many detection models. Our experiments are based on the representative one-stage detection model RetinaNet. In the Common Objects in Context (COCO) dataset, when ResNet50 and ResNet101 are used as backbone networks, the detection performances can be increased by 0.4 and 0.5% AP, respectively. When the DSA module and object confidence task are both applied in RetinaNet, the detection performances based on ResNet50 and ResNet101 can be increased by 1.0 and 1.4% AP, respectively. The experiment results show the effectiveness of the DSA module.
Forgiveness and the Naturalistic Approach to Religion: A Contextual View of the Problem of Evil
Authors: Oleksowicz Michał , Huzarek Tomasz
Published: September 2021

Cognitive Science of Religion and evolutionary approaches in the study of religion have opened the rapidly developing field of naturalistic explanation of religion. Since its inception, this empirically driven project has undergone a slow evolution, giving rise to the view that explaining religion is not a matter of accounting for a single (cognitive or functional) trait, but rather involves explaining a very complex repertoire of patterns of thinking and behavior. In this paper, we would like to provide a philosophical analysis of the highly complex problem of forgiveness from the Christian religious and naturalistic perspectives. Our analysis demonstrates a crucial way to understand the concepts of guilt, forgiveness and reconciliation as discussed in the context of Christian theology. At the same time, we also discuss certain strengths and weaknesses of the naturalistic accounts. Finally, we formulate some suggestions for advancing the science–religion dialogue on the problem of evil.
Quality Scoring of the Fengyun 4A Clear Sky Radiance Product
Authors: Yu Tianlei , Ma Gang , Lu Feng , Zhang Xiaohu , Zhang Peng
Published: September 2021

The Clear Sky Radiance (CSR) product has been widely used instead of Level 1 (L1) geostationary imager data in data assimilation for numerical weather prediction due to its many advantages concerning superobservation methodology. In this study, CSR was produced in two water vapor channels (channels 9 and channel 10, with wavelengths at 5.8–6.7 μm and 6.9–7.3 μm) of the Advanced Geostationary Radiation Imager aboard Fengyun 4A. The root mean square error (RMSE) between CSR observations and backgrounds was used as a quality flag and was predicted by cloud cover, standard deviation (STD), surface type, and elevation of a CSR field of view (FOV). Then, a centesimal scoring system based on the predicted RMSE was set to a CSR FOV that indicates its percentile point in the quality distribution of the whole FOV. Validations of the scoring system demonstrated that the biases of the predicted RMSE were small for all FOVs and that the score was consistent with the predicted RMSE, especially for FOVs with high scores. We suggest using this score for quality control (QC) to replace the QC of cloud cover, STD, and elevation of CSR, and we propose 40 points as the QC threshold for the two channels, above which the predicted RMSE of a CSR is superior to the RMSE of averaged clear-sky L1 data.
Change Detection of Building Objects in High-Resolution Single-Sensor and Multi-Sensor Imagery Considering the Sun and Sensor’s Elevation and Azimuth Angles
Authors: Jung Sejung , Lee Won Hee , Han Youkyung
Published: September 2021

Building change detection is a critical field for monitoring artificial structures using high-resolution multitemporal images. However, relief displacement depending on the azimuth and elevation angles of the sensor causes numerous false alarms and misdetections of building changes. Therefore, this study proposes an effective object-based building change detection method that considers azimuth and elevation angles of sensors in high-resolution images. To this end, segmentation images were generated using a multiresolution technique from high-resolution images after which object-based building detection was performed. For detecting building candidates, we calculated feature information that could describe building objects, such as rectangular fit, gray-level co-occurrence matrix (GLCM) homogeneity, and area. Final building detection was then performed considering the location relationship between building objects and their shadows using the Sun’s azimuth angle. Subsequently, building change detection of final building objects was performed based on three methods considering the relationship of the building object properties between the images. First, only overlaying objects between images were considered to detect changes. Second, the size difference between objects according to the sensor’s elevation angle was considered to detect the building changes. Third, the direction between objects according to the sensor’s azimuth angle was analyzed to identify the building changes. To confirm the effectiveness of the proposed object-based building change detection performance, two building density areas were selected as study sites. Site 1 was constructed using a single sensor of KOMPSAT-3 bitemporal images, whereas Site 2 consisted of multi-sensor images of KOMPSAT-3 and unmanned aerial vehicle (UAV). The results from both sites revealed that considering additional shadow information showed more accurate building detection than using feature information only. Furthermore, the results of the three object-based change detections were compared and analyzed according to the characteristics of the study area and the sensors. Accuracy of the proposed object-based change detection results was achieved over the existing building detection methods.
Monitoring Water and Energy Cycles at Climate Scale in the Third Pole Environment (CLIMATE-TPE)
Authors: Su Zhongbo , Ma Yaoming , Chen Xuelong , Dong Xiaohua , Du Junping , Han Cunbo , He Yanbo , Hofste Jan G. , Li Maoshan , Li Mengna , Lv Shaoning , Ma Weiqiang , Polo María J. , Peng Jian , Qian Hui , Sobrino Jose , van der Velde Rogier , Wen Jun , Wang Binbin , Wang Xin , Yu Lianyu , Zhang Pei , Zhao Hong , Zheng Han , Zheng Donghai , Zhong Lei , Zeng Yijian
Published: September 2021

A better understanding of the water and energy cycles at climate scale in the Third Pole Environment is essential for assessing and understanding the causes of changes in the cryosphere and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and for predicting the possible changes in water resources in South and East Asia. This paper reports the following results: (1) A platform of in situ observation stations is briefly described for quantifying the interactions in hydrosphere-pedosphere-atmosphere-cryosphere-biosphere over the Tibetan Plateau. (2) A multiyear in situ L-Band microwave radiometry of land surface processes is used to develop a new microwave radiative transfer modeling system. This new system improves the modeling of brightness temperature in both horizontal and vertical polarization. (3) A multiyear (2001–2018) monthly terrestrial actual evapotranspiration and its spatial distribution on the Tibetan Plateau is generated using the surface energy balance system (SEBS) forced by a combination of meteorological and satellite data. (4) A comparison of four large scale soil moisture products to in situ measurements is presented. (5) The trajectory of water vapor transport in the canyon area of Southeast Tibet in different seasons is analyzed, and (6) the vertical water vapor exchange between the upper troposphere and the lower stratosphere in different seasons is presented.
Identifying Potential Landslides by Stacking-InSAR in Southwestern China and Its Performance Comparison with SBAS-InSAR
Authors: Zhang Lele , Dai Keren , Deng Jin , Ge Daqing , Liang Rubing , Li Weile , Xu Qiang
Published: September 2021

Landslide disasters occur frequently in the mountainous areas in southwest China, which pose serious threats to the local residents. Interferometry Synthetic Aperture Radar (InSAR) provides us the ability to identify active slopes as potential landslides in vast mountainous areas, to help prevent and mitigate the disasters. Quickly and accurately identifying potential landslides based on massive SAR data is of great significance. Taking the national highway near Wenchuan County, China, as study area, this paper used a Stacking-InSAR method to quickly and qualitatively identify potential landslides based on a total of 40 Sentinel SAR images acquired from November 2017 to March 2019. As a result, 72 active slopes were successfully detected as potential landslides. By comparing the results from Stacking-InSAR with the results from the traditional SBAS-InSAR (Small Baselines Subset) time series method, it was found that the two methods had a high consistency, with 81.7% potential landslides identified by both of the two methods. A detailed comparison on the detection differences was performed, revealing that Stacking-InSAR, compared to SBAS-InSAR may miss a few active slopes with small spatial scales, small displacement levels and the ones affected by the atmosphere, while it has good performance on poor-coherence regions, with the advantages of low technical requirements and low computation labor. The Stacking-InSAR method would be a fast and powerful method to qualitatively and effectively identify potential landslides in vast mountainous areas, with a comprehensive understanding of its specialty and limitations.
Optical Fiber Sensors for Structural Monitoring in Power Transformers
Authors: Monteiro Catarina S. , Rodrigues António V. , Viveiros Duarte , Linhares Cassiano , Mendes Hélder , Silva Susana O. , Marques Paulo V. S. , Tavares Sérgio M. O. , Frazão Orlando
Published: September 2021

Power transformers are central elements of power transmission systems and their deterioration can lead to system failures, causing major disruptions in service. Catastrophic failures can occur, posing major environmental hazards due to fires, explosions, or oil spillage. Early fault detection can be accomplished or estimated using electrical sensors or a chemical analysis of oil or gas samples. Conventional methods are incapable of real-time measurements with a low electrical noise due to time-consuming analyses or susceptibility to electromagnetic interference. Optical fiber sensors, passive elements that are immune to electromagnetic noise, are capable of structural monitoring by being enclosed in power transformers. In this work, optical fiber sensors embedded in 3D printed structures are studied for vibration monitoring. The fiber sensor is encapsulated between two pressboard spacers, simulating the conditions inside the power transformer, and characterized for vibrations with frequencies between 10 and 800 Hz, with a constant acceleration of 10 m/s2. Thermal aging and electrical tests are also accomplished, aiming to study the oil compatibility of the 3D printed structure. The results reported in this work suggest that structural monitoring in power transformers can be achieved using optical fiber sensors, prospecting real-time monitoring.
A Magnetic Field SPR Sensor Based on Temperature Self-Reference
Authors: Mo Xinwei , Lv Jiangtao , Liu Qiang , Jiang Xiaoxiao , Si Guangyuan
Published: September 2021

In this paper, a novel D-shaped photonic crystal fiber sensor for simultaneous measurements of magnetic field and temperature is proposed and characterized. Based on the surface plasmon resonance theory, the D-shaped flat surface coated with a gold layer is in direct contact with magnetic fluid to detect magnetic field, and one of the relatively small air holes near the fiber core is filled with polydimethylsiloxane (PDMS) to sense temperature. The realization of measuring the magnetic field and temperature separately through two channels depends on the fact that the magnetic field only changes the refractive index of the magnetic fluid, but has no effect on the refractive index of PDMS. The refractive index of the magnetic fluid and PDMS can be affected by temperature at the same time. The sensor designed in this work can separate the variations of the magnetic field and temperature simultaneously, therefore solving the cross-sensitivity problem to further improve the magnetic field sensitivity. When the thickness of the gold film is 50 nm and the radius of the filling hole is 0.52 µm, the magnetic field sensitivity and the temperature sensitivity of magnetic field sensor based on temperature self-reference can reach 0.14274 nm/Oe and −0.229 nm/°C, respectively.
On the Importance of Characterizing Virtual PMUs for Hardware-in-the-Loop and Digital Twin Applications
Authors: Mingotti Alessandro , Costa Federica , Cavaliere Diego , Peretto Lorenzo , Tinarelli Roberto
Published: September 2021

In recent years, the introduction of real-time simulators (RTS) has changed the way of researching the power network. In particular, researchers and system operators (SOs) are now capable of simulating the complete network and of making it interact with the real world thanks to the hardware-in-the-loop (HIL) and digital twin (DT) concepts. Such tools create infinite scenarios in which the network can be tested and virtually monitored to, for example, predict and avoid faults or energy shortages. Furthermore, the real-time monitoring of the network allows estimating the status of the electrical assets and consequently undertake their predictive maintenance. The success of the HIL and DT application relies on the fact that the simulated network elements (cables, generation, accessories, converters, etc.) are correctly modeled and characterized. This is particularly true if the RTS acquisition capabilities are used to enable the HIL and the DT. To this purpose, this work aims at emphasizing the role of a preliminary characterization of the virtual elements inside the RTS system, experimentally verifying how the overall performance is significantly affected by them. To this purpose, a virtual phasor measurement unit (PMU) is tested and characterized to understand its uncertainty contribution. To achieve that, firstly, the characterization of a virtual PMU calibrator is described. Afterward, the virtual PMU calibration is performed, and the results clearly highlight its key role in the overall uncertainty. It is then possible to conclude that the characterization of the virtual elements, or models, inside RTS systems (omitted most of the time) is fundamental to avoid wrong results. The same concepts can be extended to all those fields that exploit HIL and DT capabilities.
Methods of Hidden Periodicity Discovering for Gearbox Fault Detection
Authors: Javorskyj Ihor , Matsko Ivan , Yuzefovych Roman , Lychak Oleh , Lys Roman
Published: September 2021

It is shown that the models of gear pair vibration, proposed in literature, are particular cases of the bi-periodically correlated random processes (BPCRPs), which describe its stochastic recurrence with two periods. The possibility of vibration and analysis within the framework of BPCRP approximation, in the form of periodically correlated random processes (PCRPs), is grounded and the implementation of vibration processing procedures using PCRP techniques, which are worked out by the authors, is given. Searching for hidden periodicities of the first and the second orders was considered as the main issue of this approach. The estimation of the non-stationary period (basic frequency) allowed us to carry out a detailed analysis of the deterministic part, the covariance structure of the stochastic part, and to form, using their parameters, the sensitive indicators for fault detection. The results of the processing of the wind turbine gearbox vibration signals are presented. The amplitude spectra of the deterministic oscillations and the time changes of the stochastic part power for different fault stages are analyzed. The most efficient indicators, which are formed using the amplitude spectra for practical applications, are proposed. The presented approach was compared with known in literature cyclostationary analysis and envelope techniques, and its advantages are shown.
Robust Pressure Sensor in SOI Technology with Butterfly Wiring for Airfoil Integration
Authors: Haus Jan Niklas , Schwerter Martin , Schneider Michael , Gäding Marcel , Leester-Schädel Monika , Schmid Ulrich , Dietzel Andreas
Published: September 2021

Current research in the field of aviation considers actively controlled high-lift structures for future civil airplanes. Therefore, pressure data must be acquired from the airfoil surface without influencing the flow due to sensor application. For experiments in the wind and water tunnel, as well as for the actual application, the requirements for the quality of the airfoil surface are demanding. Consequently, a new class of sensors is required, which can be flush-integrated into the airfoil surface, may be used under wet conditions—even under water—and should withstand the harsh environment of a high-lift scenario. A new miniature silicon on insulator (SOI)-based MEMS pressure sensor, which allows integration into airfoils in a flip-chip configuration, is presented. An internal, highly doped silicon wiring with “butterfly” geometry combined with through glass via (TGV) technology enables a watertight and application-suitable chip-scale-package (CSP). The chips were produced by reliable batch microfabrication including femtosecond laser processes at the wafer-level. Sensor characterization demonstrates a high resolution of 38 mVV−1 bar−1. The stepless ultra-smooth and electrically passivated sensor surface can be coated with thin surface protection layers to further enhance robustness against harsh environments. Accordingly, protective coatings of amorphous hydrogenated silicon nitride (a-SiN:H) and amorphous hydrogenated silicon carbide (a-SiC:H) were investigated in experiments simulating environments with high-velocity impacting particles. Topographic damage quantification demonstrates the superior robustness of a-SiC:H coatings and validates their applicability to future sensors.
Optoacoustic Sensing of Surfactant Crude Oil in Thermal Relaxation and Nonlinear Regimes
Authors: Subochev Pavel , Kurnikov Alexey , Sergeeva Ekaterina , Kirillin Mikhail , Kapustin Ivan , Belyaev Roman , Ermoshkin Alexey , Molkov Alexander
Published: September 2021

We propose a laser optoacoustic method for the complex characterization of crude oil pollution of the water surface by the thickness of the layer, the speed of sound, the coefficient of optical absorption, and the temperature dependence of the Grüneisen parameter. Using a 532 nm pulsed laser and a 1–100 MHz ultra-wideband ultrasonic antenna, we have demonstrated the capability of accurate (>95%) optoacoustic thickness measurements in the 5 to 500-micron range, covering 88% of slicks observed during 2010 oil spill in the Gulf of Mexico. In the thermal relaxation regime of optoacoustic measurements, the value of optical absorption coefficient (30 mm−1) agreed with the data of independent spectrophotometric measurements, while the sound speed (1430 m/s) agreed with the tabular data. When operating in a nonlinear regime, the effect of local deformation of the surface of the oil film induced by heating laser radiation was revealed. The dose-time parameters of laser radiation ensuring the transition from the thermal relaxation regime of optoacoustic generation to nonlinear one were experimentally investigated. The developed OA method has potential for quantitative characterization of not only the volume, but also the degree and even the type of oil pollution of the water surface.
An Extended Modular Processing Pipeline for Event-Based Vision in Automatic Visual Inspection
Authors: Beck Moritz , Maier Georg , Flitter Merle , Gruna Robin , Längle Thomas , Heizmann Michael , Beyerer Jürgen
Published: September 2021

Dynamic Vision Sensors differ from conventional cameras in that only intensity changes of individual pixels are perceived and transmitted as an asynchronous stream instead of an entire frame. The technology promises, among other things, high temporal resolution and low latencies and data rates. While such sensors currently enjoy much scientific attention, there are only little publications on practical applications. One field of application that has hardly been considered so far, yet potentially fits well with the sensor principle due to its special properties, is automatic visual inspection. In this paper, we evaluate current state-of-the-art processing algorithms in this new application domain. We further propose an algorithmic approach for the identification of ideal time windows within an event stream for object classification. For the evaluation of our method, we acquire two novel datasets that contain typical visual inspection scenarios, i.e., the inspection of objects on a conveyor belt and during free fall. The success of our algorithmic extension for data processing is demonstrated on the basis of these new datasets by showing that classification accuracy of current algorithms is highly increased. By making our new datasets publicly available, we intend to stimulate further research on application of Dynamic Vision Sensors in machine vision applications.
Sub-Frame Evaluation of Frame Synchronization for Camera Network Using Linearly Oscillating Light Spot
Authors: Kim Hyuno , Ishikawa Masatoshi
Published: September 2021

Precisely evaluating the frame synchronization of the camera network is often required for accurate data fusion from multiple visual information. This paper presents a novel method to estimate the synchronization accuracy by using inherent visual information of linearly oscillating light spot captured in the camera images instead of using luminescence information or depending on external measurement instrument. The suggested method is compared to the conventional evaluation method to prove the feasibility. Our experiment result implies that the estimation accuracy of the frame synchronization can be achieved in sub-millisecond order.
Routing with Face Traversal and Auctions Algorithms for Task Allocation in WSRN
Authors: Stanulovic Jelena , Mitton Nathalie , Mezei Ivan
Published: September 2021

Four new algorithms (RFTA1, RFTA2, GFGF2A, and RFTA2GE) handling the event in wireless sensor and robot networks based on the greedy-face-greedy (GFG) routing extended with auctions are proposed in this paper. In this paper, we assume that all robots are mobile, and after the event is found (reported by sensors), the goal is to allocate the task to the most suitable robot to act upon the event, using either distance or the robots’ remaining energy as metrics. The proposed algorithms consist of two phases. The first phase of algorithms is based on face routing, and we introduced the parameter called search radius (SR) at the end of this first phase. Routing is considered successful if the found robot is inside SR. After that, the second phase, based on auctions, is initiated by the robot found in SR trying to find a more suitable one. In the simulations, network lifetime and communication costs are measured and used for comparison. We compare our algorithms with similar algorithms from the literature (k-SAAP and BFS) used for the task assignment. RFTA2 and RFTA2GE feature up to a seven-times-longer network lifetime with significant communication overhead reduction compared to k-SAAP and BFS. Among our algorithms, RFTA2GE features the best robot energy utilization.
Thermal Imaging Metrology Using High Dynamic Range Near-Infrared Photovoltaic-Mode Camera
Authors: Rockett Thomas B. O. , Boone Nicholas A. , Richards Robert D. , Willmott Jon R.
Published: September 2021

The measurement of a wide temperature range in a scene requires hardware capable of high dynamic range imaging. We describe a novel near-infrared thermal imaging system operating at a wavelength of 940 nm based on a commercial photovoltaic mode high dynamic range camera and analyse its measurement uncertainty. The system is capable of measuring over an unprecedently wide temperature range; however, this comes at the cost of a reduced temperature resolution and increased uncertainty compared to a conventional CMOS camera operating in photodetective mode. Despite this, the photovoltaic mode thermal camera has an acceptable level of uncertainty for most thermal imaging applications with an NETD of 4–12 °C and a combined measurement uncertainty of approximately 1% K if a low pixel clock is used. We discuss the various sources of uncertainty and how they might be minimised to further improve the performance of the thermal camera. The thermal camera is a good choice for imaging low frame rate applications that have a wide inter-scene temperature range.
Graphical Optimization of Spectral Shift Reconstructions for Optical Backscatter Reflectometry
Authors: Sweeney Daniel C. , Sweeney Dennis M. , Petrie Christian M.
Published: September 2021

Optical backscatter reflectometry (OBR) is an interferometric technique that can be used to measure local changes in temperature and mechanical strain based on spectral analyses of backscattered light from a singlemode optical fiber. The technique uses Fourier analyses to resolve spectra resulting from reflections occurring over a discrete region along the fiber. These spectra are cross-correlated with reference spectra to calculate the relative spectral shifts between measurements. The maximum of the cross-correlated spectra—termed quality—is a metric that quantifies the degree of correlation between the two measurements. Recently, this quality metric was incorporated into an adaptive algorithm to (1) selectively vary the reference measurement until the quality exceeds a predefined threshold and (2) calculate incremental spectral shifts that can be summed to determine the spectral shift relative to the initial reference. Using a graphical (network) framework, this effort demonstrated the optimal reconstruction of distributed OBR measurements for all sensing locations using a maximum spanning tree (MST). By allowing the reference to vary as a function of both time and sensing location, the MST and other adaptive algorithms could resolve spectral shifts at some locations, even if others can no longer be resolved.
Development of a Simple High-Performance Liquid Chromatography-Based Method to Quantify Synergistic Compounds and Their Composition in Dried Leaf Extracts of Piper Sarmentosum Roxb.
Authors: Purba Rayudika , Paengkoum Siwaporn , Paengkoum Pramote
Published: September 2021

There is a growing demand to enhance pharmaceutical and food safety using synergistic compounds from Piper sarmentosum Roxb., such as polyphenols and water-soluble vitamins. However, information on standardized analytical methods to identify and quantify these compounds of interest is limited. A reversed-phase high-performance liquid chromatography with diode-array detection (HPLC-DAD)-based method was developed to simultaneously detect and quantify the amounts of tannin, flavonoid, cinnamic acid, essential oil, and vitamins extracted from P. sarmentosum leaves using methanol, chloroform, and hexane. Commercially and non-commercially-cultivated P. sarmentosum leaves were subjected to seven different drying treatments (shade; sun; air oven at 40 °C, 60 °C, 80 °C, and 100 °C; and freeze-drying) for three consecutive months. Most compounds were detected most efficiently at a detection wavelength of 272 nm. The developed method displayed good detection limits (LOD, 0.026–0.789 µg/mL; LOQ, 0.078–2.392 µg/mL), linearity (R2 > 0.999), precision (%RSD, <1.00), and excellent accuracy (96–102%). All P. sarmentosum leaf extracts were simultaneously tested and analytically compared without time-consuming fractionation. Methanolic plant extracts showed better peak area and retention time splits compared to chloroformic and hexanoic extracts. Differences in synergistic compound composition were dependent on the type of drying treatment but not on cultivation site and time of sampling. Flavonoid was identified as the dominant phytochemical component in P. sarmentosum leaves, followed by the essential oil, cinnamic acid, ascorbic acid, and tannin. Overall, we present a simple and reproducible chromatographic method that can be applied to identify different plant compounds.
Digital Transformation and the New Normal in China: How Can Enterprises Use Digital Technologies to Respond to COVID-19?
Authors: Lee Ching-Hung , Wang Dianni , Desouza Kevin C. , Evans Richard
Published: September 2021

The COVID-19 pandemic, a worldwide health and humanitarian crisis, has created unique challenges for citizens, governments, and organizations alike. Business leaders ask ‘what is the new normal, post-pandemic?’ while industries become more complex and uncertain. Premises sit empty, employees work remotely, and customers possess less disposable income. However bleak, opportunities do exist. Organizations will, however, need to transform. Technology will need to be used to respond to the pandemic, and organizations must re-structure to better function. This paper examines the role that digital technologies can play in responding to pandemics and outlines four classifications of digital technologies for pandemic response. An as-is/to-be pathway analysis is presented using case studies from Chinese enterprises to provide trajectory guidance for moving forward to the new normal. After analysis from an incorporated technology-centric and business model-based framework perspective, six fundamental enterprise strategies are presented that are derived from literature and empirical observations.
Lipids from Hermetia illucens, an Innovative and Sustainable Source
Authors: Franco Antonio , Scieuzo Carmen , Salvia Rosanna , Petrone Anna Maria , Tafi Elena , Moretta Antonio , Schmitt Eric , Falabella Patrizia
Published: September 2021

The exponential increase of global demand for proteins and lipids can no longer be satisfied by classical sources. High amounts of CO2 produced by intensive livestock breeding and its effects on the environment are the main factors that prevent the use of animals as primary sources for proteins and lipids, calling for the use of new sustainable sources, such as insects. The massive breeding of bioconverter insects as a feed source has been a major topic in recent years, with both economic and scientific aspects related to rearing and subsequent processing optimization. The larvae of Hermetia illucens (Diptera: Stratiomyidae) (also known as Black Soldier Fly) can be used for the eco-sustainable production of proteins and lipids with high biological and economic value. Lipids can be obtained from BSF bioconversion processes and are present in high quantities in the last instar larvae and prepupae. Fats obtained from BSF are used as animal feed ingredients, in the formulation of several products for personal care, and in biodiesel production. To enable the use of insect-derived lipids, it is important to understand how to optimize their extraction. Here, we summarize the published information on the composition, the extraction methods, and the possible applications of the BSF lipid component.
Transition to the Circular Economy in the Fashion Industry: The Case of the Inditex Family Business
Authors: Esbeih Karina Nicolle , Molina-Moreno Valentín , Núñez-Cacho Pedro , Silva-Santos Bruna
Published: September 2021

Society is increasingly concerned about aspects of work related to sustainability. This leads organizations to reflect on the economic, environmental, and social problems that affect both current and future generations. When companies identify an environmental problem, they try to respond to it through changes in their environmental policies, aiming at the transition towards sustainability. In this context, the circular economy appears as a regenerative industrial system that replaces the concept of “end of life” with that of “restoration”. It is oriented to the use of renewable energies, eliminating the use of toxic chemicals, which are harmful to reuse. The theory of socio-emotional wealth describes the behavior patterns of family businesses in response to the environmental changes that occur and the reasons derived from the family character that make them move towards the circular economy model. This article studies the case of the Spanish textile manufacturing and distribution multinational Inditex, analyzing the information collected in its environmental balances in the period 2013–2018. The analysis allows us to observe the speed of Inditex’s transition to the circular economy. For this, transition speed indicators were formed in each of the dimensions of the circular economy model. The results of the study indicate areas in which the company is moving faster and those in which more effort is needed. Finally, a collection of good practices related to the CE used by Inditex is provided.
Pedagogical Approaches for Sustainable Development in Building in Higher Education
Authors: Martín-Garin Alexander , Millán-García José Antonio , Leon Iñigo , Oregi Xabat , Estevez Julian , Marieta Cristina
Published: September 2021

Education for sustainable development (ESD) is one of the great challenges that university faculties have to face. Therefore, a multidisciplinary team from the faculty of Engineering of Gipuzkoa (EIG) at the University of the Basque Country (UPV/EHU) has developed pedagogical approaches to apply in construction degrees, namely Civil Engineering and Technical Architecture. Pedagogical tools, such as problem-based learning (PBL) or research-based learning (RBL), and environmental tools, such as the life cycle assessment (LCA) and computational thinking (CT), have been used; in doing so, they acquire a sustainable approach to work “soft-skills” competencies into sustainability. For example, research-based tools have helped to revalorize waste both outside and inside the university; they have contributed to more sustainable industrial processes, collaborative research projects, and participation in conferences and scientific publications. Based on academic results, the designed tools are appropriate for teaching in Technical Architecture and Civil Engineering degrees; however, to demonstrate their potential in terms of sustainable education, holistic rubrics based on in-depth quantitative educational research are required. Thus, to analyze the ability of the students to incorporate sustainability principles in their work, the multidisciplinary team presenting this paper plans to collaborate with psychologists and sociologists within the framework of the Bizia-Lab program of the UPV/EHU.
Food Insecurity and Related Factors among Farming Families in Takhar Region, Afghanistan
Authors: Samim Sayed Alim , Hu Zhiquan , Stepien Sebastian , Amini Sayed Younus , Rayee Ramin , Niu Kunyu , Mgendi George
Published: September 2021

Improved food security remains a major challenge for policymakers in Afghanistan. The objective of this study is to investigate the prevalence and drivers of food insecurity among farming households in the Takhar region of Afghanistan. Household questionnaire survey datasets were obtained from 262 farmers via multi-stage sampling across four districts. The Household Food Insecurity Access Scale (HFIAS) was constructed to assess the prevalence of food insecurity, and an ordered probit econometric model was used to identify the factors influencing the prevalence rates in farming families. The findings indicate that 66.79% of the farming households were food insecure, whilst 30.53% were severely food insecure. After adjustment of socio-economic and demographic characteristics of families, the ordered probit results reveals that household head education, dependency ratio, farm income, access to non-agricultural income, livestock unit, group membership, borrowing, farm diseases, flood, and war significantly influenced farming households’ food insecurity in the study area. Our findings highlight the urgent requirement for policies and initiatives to support farmers to improve their overall food security. Such strategies should focus on introducing improved farming techniques, enhancing farmer education levels, livestock development programs, building and empowering farmers groups, creating credit access to households, and providing humanitarian food support.