bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancement of Imaging Quality of Interferenceless Coded Aperture Correlation Holography Based on Physics-Informed Deep Learning
Authors: Xiong Rui , Zhang Xiangchao , Ma Xinyang , Qi Lili , Li Leheng , Jiang Xiangqian
Published: December 2022

Interferenceless coded aperture correlation holography (I-COACH) was recently introduced for recording incoherent holograms without two-wave interference. In I-COACH, the light radiated from an object is modulated by a pseudo-randomly-coded phase mask and recorded as a hologram by a digital camera without interfering with any other beams. The image reconstruction is conducted by correlating the object hologram with the point spread hologram. However, the image reconstructed by the conventional correlation algorithm suffers from serious background noise, which leads to poor imaging quality. In this work, via an effective combination of the speckle correlation and neural network, we propose a high-quality reconstruction strategy based on physics-informed deep learning. Specifically, this method takes the autocorrelation of the speckle image as the input of the network, and switches from establishing a direct mapping between the object and the image into a mapping between the autocorrelations of the two. This method improves the interpretability of neural networks through prior physics knowledge, thereby remedying the data dependence and computational cost. In addition, once a final model is obtained, the image reconstruction can be completed by one camera exposure. Experimental results demonstrate that the background noise can be effectively suppressed, and the resolution of the reconstructed images can be enhanced by three times.
Effect of Lidar Receiver Field of View on UAV Detection
Authors: Chen Zijian , Miao Yu , Tang Dan , Yang Hao , Pan Wenwu
Published: December 2022

Researchers have shown that single-photon light detection and ranging (lidar) is highly sensitive and has a high temporal resolution. Due to the excellent beam directivity of lidar, most applications focus on ranging and imaging. Here, we present a lidar detection system for night environments. Different from MEMS, we choose a large divergence rather than scanning to detect unmanned aerial vehicles (UAVs). Collection and detection are achieved through the use of high-efficiency optical devices. With time-correlated single photon counting (TCSPC), we performed subsequent drone search work at centimeter resolution. We believe that we have developed a new technique for detecting UAVs. We show how the field of view influences the detection process. For some key areas of air defense, it is extremely necessary to find UAVs quickly and in a timely manner. In short, the results represent an important step toward practical, low-power drone detection using lidar.
Remote Sensing Extraction Method of Illicium verum Based on Functional Characteristics of Vegetation Canopy
Authors: Zhang Zhuoyao , Liu Xiangnan , Zhu Lihong , Li Junji , Zhang Yue
Published: December 2022

With the rapid development of remote sensing technology, researchers have attempted to improve the accuracy of tree species classifications from both data sources and methods. Although previous studies on tree species recognition have utilized the spectral and textural features of remote sensing images, they are unable to effectively extract tree species due to the problems of “same object with different spectrum” and “foreign object with the same spectrum”. Therefore, this study introduces vegetation functional datasets to further improve tree species classification. Using vegetation functional datasets, Sentinel-2 (S2) spectral datasets, and environmental datasets, combined with a Random Forest (RF) model, the classification of six types of land cover in Leye, Guangxi was completed and the planting distribution of Illicium verum in Leye County was extracted. Our results showed that the combination of vegetation functional datasets, S2 spectral datasets, and environmental datasets provided the highest overall accuracy (OA) (0.8671), Kappa coefficient (0.8382), and F1-Score (0.79). We believe that the vegetation functional datasets can enhance the accuracy of Illicium verum classification and provide new directions for tree species identification research. If vegetation functional datasets from more tree species are obtained in the future, we can extend them to the level of multiple tree species, and this approach may help to extract more information about forest species from remote sensing data in future studies.
MQANet: Multi-Task Quadruple Attention Network of Multi-Object Semantic Segmentation from Remote Sensing Images
Authors: Li Yuxia , Si Yu , Tong Zhonggui , He Lei , Zhang Jinglin , Luo Shiyu , Gong Yushu
Published: December 2022

Multi-object semantic segmentation from remote sensing images has gained significant attention in land resource surveying, global change monitoring, and disaster detection. Compared to other application scenarios, the objects in the remote sensing field are larger and have a wider range of distribution. In addition, some similar targets, such as roads and concrete-roofed buildings, are easily misjudged. However, existing convolutional neural networks operate only in the local receptive field, and this limits their capacity to represent the potential association between different objects and surrounding features. This paper develops a Multi-task Quadruple Attention Network (MQANet) to address the above-mentioned issues and increase segmentation accuracy. The MQANet contains four attention modules: position attention module (PAM), channel attention module (CAM), label attention module (LAM), and edge attention module (EAM). The quadruple attention modules obtain global features by expanding the receptive fields of the network and introducing spatial context information in the label. Then, a multi-tasking mechanism which splits a multi-category segmentation task into several binary-classification segmentation tasks is introduced to improve the ability to identify similar objects. The proposed MQANet network was applied to the Potsdam dataset, the Vaihingen dataset and self-annotated images from Chongzhou and Wuzhen (CZ-WZ), representative cities in China. Our MQANet performs better over the baseline net by a large margin of +6.33 OA and +7.05 Mean F1-score on the Vaihingen dataset, +3.57 OA and +2.83 Mean F1-score on the Potsdam dataset, and +3.88 OA and +8.65 Mean F1-score on the self-annotated dataset (CZ-WZ dataset). In addition, each image execution time of the MQANet model is reduced 66.6 ms compared to UNet. Moreover, the effectiveness of MQANet was also proven by comparative experiments with other studies.
Activity of Okgye Limestone Mine in South Korea Observed by InSAR Coherence and PSInSAR Techniques
Authors: Lee Hoseung , Moon Jihyun , Lee Hoonyol
Published: December 2022

The Okgye limestone mine, which is the largest open-pit limestone mine located in a mountainous area in Korea, suffered a collapse in 2012 that claimed four casualties. Restoration work on the rocky mined-out slopes, as well as mining and dumping activities, are still in progress. Monitoring slope stability is important to prevent the sudden collapse of slopes, which can be efficiently performed by satellite-based interferometric synthetic aperture radar (InSAR) techniques. Firstly, we obtained elevation changes using InSAR-generated Copernicus 30 m DEM in 2014 and an SRTM 1Sec DEM in 2000, through which the area was roughly classified into the mining area, tailings storage area, and the mined-out area. A time series of 12-day coherence images produced by Sentinel-1B SAR were averaged annually to produce an RGB-composite image to observe the change in mining activities during 2018, 2019, and 2020. We found many persistent scatterers (PS) when observing the ground displacement, both in the ascending and descending orbits, from which we decomposed this into the vertical and east components. The largest displacement of 63.6 mm/year was observed during 2019 and 2020 in the tailings storage area in the direction of the dumping slope. For the rocky outcrops and the transmission tower, we found a seasonal oscillation, which can be interpreted as the thermal expansion of limestone and iron. This paper demonstrated that the surface stability and deformation of open-pit mines could be effectively monitored by combining InSAR DEM, coherence, and PSInSAR techniques.
Recent 50-Year Glacier Mass Balance Changes over the Yellow River Source Region, Determined by Remote Sensing
Authors: Zhou Min , Xu Song , Wang Yetang , Wang Yuzhe , Hou Shugui
Published: December 2022

The A’nyêmaqên Mountains have the largest concentration of glaciers in the Yellow River basin, which play a crucial role in regulating the runoff regime of the Yellow River. Thus, the quantification of glacier mass balance and its effects on river runoff is greatly required. However, current studies mainly focus on mass changes since 2000. Here, we report for the first time region-wide glacier elevation and mass changes, which were derived from digital elevation models (DEMs) produced from historical topographic maps (TOPO), SRTM retrievals, and ASTER L1A stereo imagery spanning the past 50 years. The results indicated a negative mass balance (−0.24 ± 0.05 m w.e. a−1) of all glaciers for the 1966–2018 timespan. The mass loss rapidly accelerated from −0.16 ± 0.09 m w.e. a−1 in 1966–2000 to −0.36 ± 0.06 m w.e. a−1 during the period from 2000–2018. The rise in mass loss rate from 2000 onwards was mainly associated with the rapidly increased summer warming.
Machine Learning-Based Stator Current Data-Driven PMSM Stator Winding Fault Diagnosis
Authors: Pietrzak Przemyslaw , Wolkiewicz Marcin
Published: December 2022

Permanent magnet synchronous motors (PMSMs) have become one of the most important components of modern drive systems. Therefore, fault diagnosis and condition monitoring of these machines have been the subject of many studies in recent years. This article presents an intelligent stator current-data driven PMSM stator winding fault detection and classification method. Short-time Fourier transform is applied in the process of fault feature extraction from the stator phase current symmetrical components signal. Automation of the fault detection and classification process is carried out with the use of three selected machine learning algorithms: support vector machine, naïve Bayes classifier and multilayer perceptron. The concept and online verification of the original intelligent fault diagnosis system with the potential of a real industrial deployment are demonstrated. Experimental results are presented to evaluate the effectiveness of the proposed methodology.
Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke
Authors: Barkjohn Karoline K. , Holder Amara L. , Frederick Samuel G. , Clements Andrea L.
Published: December 2022

PurpleAir particulate matter (PM) sensors are increasingly used in the United States and other countries for real-time air quality information, particularly during wildfire smoke episodes. Uncorrected PurpleAir data can be biased and may exhibit a nonlinear response at extreme smoke concentrations (>300 µg/m3). This bias and nonlinearity result in a disagreement with the traditional ambient monitoring network, leading to the public’s confusion during smoke episodes. These sensors must be evaluated during smoke-impacted times and then corrected for bias, to ensure that accurate data are reported. The nearby public PurpleAir sensor and monitor pairs were identified during the summer of 2020 and were used to supplement the data from collocated pairs to develop an extended U.S.-wide correction for high concentrations. We evaluated several correction schemes to identify an optimal correction, using the previously developed U.S.-wide correction, up to 300 µg/m3, transitioning to a quadradic fit above 400 µg/m3. The correction reduces the bias at each air quality index (AQI) breakpoint; most ambient collocations that were studied met the Environmental Protection Agency’s (EPA) performance targets (twelve of the thirteen ambient sensors met the EPA’s targets) and some smoke-impacted sites (5 out of 15 met the EPA’s performance targets in terms of the 1-h averages). This correction can also be used to improve the comparability of PurpleAir sensor data with regulatory-grade monitors when they are collectively analyzed or shown together on public information websites; the methods developed in this paper can also be used to correct future air-sensor types. The PurpleAir network is already filling in spatial and temporal gaps in the regulatory monitoring network and providing valuable air-quality information during smoke episodes.
An Immunosensor for the Determination of Cortisol in Serum and Saliva by Array SPRi
Authors: Sankiewicz Anna , Oldak Lukasz , Zelazowska-Rutkowska Beata , Hermanowicz Adam , Lukaszewski Zenon , Gorodkiewicz Ewa
Published: December 2022

Cortisol is a hormone which plays an essential role in the immune, endocrine, cardiovascular, renal and skeletal systems. Its level increases in response to stress, illness, injury or exhaustion, and it is therefore a significant diagnostic biomarker of stress. An immunosensor for the determination of cortisol by SPRi array was developed. The receptive part of the immunosensor is mouse monoclonal antibody against cortisol, immobilized via cysteamine linker. The optimum pH of the immunosensor is 7.4, and the optimum concentration of the antibody is 50 ng mL−1. The immunosensor is specific for cortisol, and its linear response ranges from 0.20 ng mL−1 (LOQ) to 8 ng mL−1. The precision of the determination was between 3.1% and 3.3%, and the recovery between 99% and 102%. The immunosensor was validated by simultaneous determination of cortisol in serum and saliva samples by a standard method, with good agreement between the results.
USV-Observed Turbulent Heat Flux Induced by Late Spring Cold Dry Air Incursion over Sub-Mesoscale Warm Regions off Sanriku, Japan
Authors: Nagano Akira , Hasegawa Takuya , Ariyoshi Keisuke , Iinuma Takeshi , Fukuda Tatsuya , Fujii Nobuhiro , Tomita Fumiaki , Hino Ryota
Published: December 2022

We performed oceanic and atmospheric observations in the region off the Sanriku coast, Japan, from May 11 to 5 July 2022, using a wave-propelled unmanned surface vehicle, a Wave Glider (WG). Despite the severe weather conditions of atmospheric low-pressure system crossings, we successfully measured wind, air temperature, humidity, and sea surface temperature over the course of 55 days to calculate the turbulent heat flux. The WG observed that the atmosphere became more humid due to the southerly wind along the northwestern rim of the North Pacific subtropical high. The warm Kuroshio water expanded to the southeast of Hokkaido as a result of the northward shedding of an anticyclonic mesoscale (~100 km) eddy, called a warm-core ring, from the Kuroshio Extension. The WG traversed smaller (sub-mesoscale) water regions that were warmer and saltier than the surrounding Kuroshio water. The observations indicate that cold, dry air masses advected by northerly winds following the passage of atmospheric low-pressure systems generate a substantial upward turbulent heat flux over sub-mesoscale warm water regions, contrasting to no heat flux in the surrounding Kuroshio water region.
Two-Photon Imaging for Non-Invasive Corneal Examination
Authors: Batista Ana , Guimarães Pedro , Domingues José Paulo , Quadrado Maria João , Morgado António Miguel
Published: December 2022

Two-photon imaging (TPI) microscopy, namely, two-photon excited fluorescence (TPEF), fluorescence lifetime imaging (FLIM), and second-harmonic generation (SHG) modalities, has emerged in the past years as a powerful tool for the examination of biological tissues. These modalities rely on different contrast mechanisms and are often used simultaneously to provide complementary information on morphology, metabolism, and structural properties of the imaged tissue. The cornea, being a transparent tissue, rich in collagen and with several cellular layers, is well-suited to be imaged by TPI microscopy. In this review, we discuss the physical principles behind TPI as well as its instrumentation. We also provide an overview of the current advances in TPI instrumentation and image analysis. We describe how TPI can be leveraged to retrieve unique information on the cornea and to complement the information provided by current clinical devices. The present state of corneal TPI is outlined. Finally, we discuss the obstacles that must be overcome and offer perspectives and outlooks to make clinical TPI of the human cornea a reality.
Evaluation of a CNN-Based Modular Precision Sprayer in Broadcast-Seeded Field
Authors: Sanchez Paolo Rommel , Zhang Hong
Published: December 2022

In recent years, machine vision systems (MVS) with convolutional neural networks (CNN) for precision spraying have been increasingly investigated due to their robust performance in plant detection. However, the high computational requirement of CNNs makes them slow to be adopted in field operations, especially in unstructured working environments such as broadcast-seeded fields. In this study, we developed a modular precision sprayer by distributing the high computational load of CNN among parallel low-cost and low-power vision computing devices. The sprayer utilized a custom precision spraying algorithm based on SSD-MobileNetV1 running on a Jetson Nano 4 GB. The model achieved 76% mAP0.5 at 19 fps for weed and soybean detection in a broadcast-seeded field. Further, the sprayer targeted all weed samples and exhibited up to 48.89% spray volume reduction with a typical walking speed up to 3.0 km/h, which was three times faster than similar systems with known targeting performance. With these results, the study demonstrated that CNN-based precision spraying in a complex broadcast-seeded field can achieve increased velocity at high accuracy without needing powerful and expensive computational hardware using modular designs.
A 3D-Printed Capacitive Smart Insole for Plantar Pressure Monitoring
Authors: Samarentsis Anastasios G. , Makris Georgios , Spinthaki Sofia , Christodoulakis Georgios , Tsiknakis Manolis , Pantazis Alexandros K.
Published: December 2022

Gait analysis refers to the systematic study of human locomotion and finds numerous applications in the fields of clinical monitoring, rehabilitation, sports science and robotics. Wearable sensors for real-time gait monitoring have emerged as an attractive alternative to the traditional clinical-based techniques, owing to their low cost and portability. In addition, 3D printing technology has recently drawn increased interest for the manufacturing of sensors, considering the advantages of diminished fabrication cost and time. In this study, we report the development of a 3D-printed capacitive smart insole for the measurement of plantar pressure. Initially, a novel 3D-printed capacitive pressure sensor was fabricated and its sensing performance was evaluated. The sensor exhibited a sensitivity of 1.19 MPa−1, a wide working pressure range (<872.4 kPa), excellent stability and durability (at least 2.280 cycles), great linearity (R2=0.993), fast response/recovery time (142–160 ms), low hysteresis (DH<10%) and the ability to support a broad spectrum of gait speeds (30–70 steps/min). Subsequently, 16 pressure sensors were integrated into a 3D-printed smart insole that was successfully applied for dynamic plantar pressure mapping and proven able to distinguish the various gait phases. We consider that the smart insole presented here is a simple, easy to manufacture and cost-effective solution with the potential for real-world applications.
Valorization of Raw Coffee Beans (Coffea arabica and Coffea canephora) through Solvent Development and Extraction of Bioactive Compounds
Authors: Ronko Letícia , Antoniassi Maria , Ueda Karina , Leal Fernando , Toci Aline , Igarashi-Mafra Luciana , Mafra Marcos , Farias Fabiane
Published: December 2022

Raw coffee beans are seen as valuable sources of bioactive compounds, such as alkaloids and chlorogenic acids. In this study, an efficient and eco-friendly method for the simultaneous extraction of caffeine, trigonelline, and chlorogenic acids from raw beans of two coffee species was developed, using green solvents and an unconventional method of extraction (assisted by ultrafast rotary disintegrator/homogenizer (UT-AE)). The experimental extraction conditions were optimized according to a completely randomized design (CRD), considering the following variables: solvent type (four deep eutectic solvents (DESs), water, and aqueous choline chloride solution (50 wt.%); temperature (25, 45, and 65 °C); and extraction technique (solid-liquid extraction with agitated heating and assisted by ultrafast rotary disintegrator/homogenizer). The extract obtained with choline chloride solution (50 wt.%) exhibited high total phenolic compounds and the highest antioxidant capacity. An analysis using high-performance liquid chromatography with a diode array detector (HPLC-DAD) indicated the presence of chlorogenic acids, caffeine, and trigonelline in all the extracts, in different amounts. The results obtained by the analysis of phenolic compounds and HPLC indicated that the aqueous solution of choline chloride (50% wt.%) was the most suitable solvent for the extraction of chlorogenic acids, while the water-based extracts showed high values of caffeine and trigonelline. DESs, in turn, seems to promote a protective effect on the antioxidant activity of biomolecules.
In Situ XRD, Raman Characterization, and Kinetic Study of CO2 Capture by Alkali Carbonate-Doped Na4SiO4
Authors: Wang Zhen , Sun Chenteng , Xu Qian , Zou Xingli , Cheng Hongwei , Lu Xionggang
Published: December 2022

Sodium silicate, a new type of CO2 sorbent, has a relatively low cost, but its sorption reactivity is not yet good enough. Alkali carbonate doping is commonly used as an effective means to improve the CO2 uptake reactivity of solid sorbents. In this study, sodium orthosilicate, Na4SiO4, was synthesized and mixed with 5, 10, and 20 mol% of Li2CO3–Na2CO3 or Li2CO3–Na2CO3–K2CO3 as CO2 sorbents. The promotion of alkali carbonates on Na4SiO4 in CO2 capture was characterized using thermal analyses in an 80 vol% CO2–20 vol% N2 atmosphere. The phase evolution and structural transformations during CO2 capture were characterized by in situ XRD and Raman, and the results showed that the intermediate pyrocarbonate, C2O52−, which emerged from alkali carbonates, enhanced the CO2 capture of Na4SiO4 to form Na2CO3 and Na2SiO3 from 100 °C. Isothermal analyses showed that 10 mol% of Li2CO3–Na2CO3 was the optimal additive for Na4SiO4 to attain better CO2 uptake performance. The alkali carbonates were effective in reducing the activation energy for both chemisorption and bulk diffusion, improving the cycle stability of Na4SiO4.
Inter-Comparisons of Major Ions and Organic Matter Using Aerodyne Aerosol Mass Spectrometer, Ion Chromatography and Sunset Lab Carbon Analyzer in Aged Aerosols from Okinawa in the Western North Pacific Rim
Authors: Kunwar Bhagawati , Torii Kazuhiro , Takami Akinori , Kawamura Kimitaka
Published: December 2022

Inorganic components were measured in the aged ambient aerosols from Cape Hedo, Okinawa, an outflow region of East Asia, using online quadrupole Aerodyne aerosol mass spectrometer (Q-AMS) and offline ion chromatography (IC) and Sunset Lab carbon analyzer. Here, we performed an inter-comparison study on nitrate (NO3−), ammonium (NH4+) and sulfate (SO42−) that were measured by IC and AMS. Sulfate and ammonium showed a good agreement between two instruments. However, abundances of NO3− by AMS are on average twice overestimated compared to nitrate obtained by IC. We also found that a significant amount of organic nitrogen (ON) was detected in the filter samples from Okinawa. The online measurement (Q-AMS) data and offline filter based-NO3− data need to be carefully evaluated when ON is abundantly present in aerosols. The OM/OC ratios derived from AMS are consistent with the bulk OMAMS/OCSunset ratios (2.1). This study demonstrates that the OM/OC of 2.1 is the reasonable criteria for more aged aerosols.
Greenhouse Gas Emissions and Carbon Sequestration from Conventional and Organic Olive Tree Nurseries in Tuscany, Italy
Authors: Lazzerini Giulio , Manzini Jacopo , Lucchetti Stefano , Nin Stefania , Nicese Francesco Paolo
Published: December 2022

In this study, conventional and organic olive tree nurseries were compared through a Life Cycle Assessment (LCA) analysis to identify processes that have a greater environmental impact and which of the two systems leads to lower greenhouse gas (GHG) emissions. Carbon sequestration in the woody biomass of the plants grown with both management systems was also considered. The research was carried out on six olive tree nurseries, four conventional and two managed also with an organic system, located in the nursery district of Pescia (Tuscany, Italy). The functional unit considered was two-year-old pot-grown plants (pot 15 cm Ø) and the results were expressed in terms of kg of CO2 equivalent (CO2eq). In all the nurseries analyzed, LCA showed that pots were the highest CO2eq emission source (45–63%), followed by potting mix (22.6–32.1%). This was due to the use of plastic in pots and peat for the growing media. Organic management was found to have a definite positive influence on the decrease of GHG, reducing the emissions up to 13% compared with conventional nurseries. Considering carbon stocked in the woody tissues of seedlings, the reduction of emissions attained 15.7% though a slightly lower (−6.7%) amount of CO2 incorporated into biomass was detected in the olive plants grown in organic nurseries. In light of our results, conversion of the nursery industry from conventional to organic management has the potential to reduce its carbon footprint.
Impact of Logistics Trends on Freight Transport Development in Urban Areas
Authors: Letnik Tomislav , Hanžič Katja , Luppino Giuseppe , Mencinger Matej
Published: December 2022

City logistics is subject to constant development, generated by new logistics trends and high customers’ expectations. With the aim of creating an effective, acceptable, and sustainable city logistics policy, it is therefore essential to understand logistics trends and their expected impact on the development of urban freight transport in the future. In this paper, we explore and compare the expectations of public authorities, business, and academia regarding the short-, medium-, and long-term impacts of different logistics trends on urban logistics. Following a literature review, the expert survey was used to assess the expected impact and time horizon. According to the respondents, “e-commerce”, “automated vehicles”, “electric vehicles”, “grey power logistics”, “omni-channel logistics”, and the “desire for speed” will have the greatest impact on urban freight transport in the future. An interesting observation concerns some differences of opinion between public and private stakeholders. In general, the business community believes that the identified trends will have a greater impact on urban logistics in a shorter period of time, while public authorities believe that the mentioned trends will have a less strong impact on urban logistics in a longer time scale. This shows the need for more active collaboration between them in the policy-making process.
Experimental Study of Deformation Measurement of Bored Pile Using OFDR and BOTDR Joint Optical Fiber Sensing Technology
Authors: Gao Lei , Qian Jiben , Han Chuan , Qin Shiwei , Feng Kunpeng
Published: December 2022

Pile foundation is the most common foundation form in geotechnical engineering; it is very important for engineering safety. In order to accurately grasp the deformation of pile foundation, OFDR (optical frequency domain reflectometer) and BOTDR (Brillouin optical time domain reflectometer) optical fiber sensing technologies are used to measure the strain variation of pile foundation. The measurement results of the two technologies are analyzed, and different data processing methods are used. The ability of the two methods to measure the strain of pile foundation is evaluated. The results show that OFDR technology can achieve high-precision and distributed measurement of strain of pile; BOTDR technology can achieve the monitoring effect of OFDR to a certain extent using appropriate data processing methods; the combination of the two methods can make up for the shortcomings of the short monitoring distance of the OFDR technique and the low accuracy of the BOTDR technique; by comparing the application effect with the two technologies in geotechnical engineering, the application prospect of OFDR–BOTDR joint optical fiber sensing technology in geotechnical engineering is discussed.
An Investigation on the Effect of Outliers for Flood Frequency Analysis: The Case of the Eastern Mediterranean Basin, Turkey
Authors: Turhan Evren
Published: December 2022

Flood frequency analysis is accepted as one of the most important applications of water resource engineering. Measurements with higher and lower values, such as outliers, can be seen in hydrological data sets based on longer observation periods that extend the overall range. This study used 50 and 25 years of annual maximum flow data from 1962 to 2011 and from 1987 to 2011 from the Stream Gauging Stations (SGS) numbered 1712, 1717, and 1721 located within the borders of the Eastern Mediterranean Basin. The flood discharges were estimated using Normal, Gumbel, and Pearson Type III probability distributions. The study adopted Kolmogorov–Smirnov (K-S) and Chi-squared goodness-of-fit tests to investigate the suitability of probability distribution functions. The maximum flow rates were obtained by utilizing Normal distribution in the 2-year and 5-year return periods for the flood values calculated with the raw data; however, after the modification of the outliers, maximum flood discharges were estimated by adopting the Pearson Type III function. While the maximum discharges for the 1717 SGS were determined using the Gumbel distribution, the Pearson Type III distribution function was utilized for the 1712 and 1721 SGSs. As a result of the K-S and Chi-squared tests, it was determined that adjustment of the outliers resulted in positive goodness-of-fit results with the Pearson Type III function.
Evolution of Rail Contact Fatigue on Crossing Nose Rail Based on Long Short-Term Memory
Authors: Kou Lei , Sysyn Mykola , Liu Jianxing , Nabochenko Olga , Han Yue , Peng Dai , Fischer Szabolcs
Published: December 2022

The share of rail transport in world transport continues to rise. As the number of trains increases, so does the load on the railway. The rails are in direct contact with the loaded wheels. Therefore, it is more easily damaged. In recent years, domestic and foreign scholars have conducted in-depth research on railway damage detection. As the weakest part of the track system, switches are more prone to damage. Assessing and predicting rail surface damage can improve the safety of rail operations and allow for proper planning and maintenance to reduce capital expenditure and increase operational efficiency. Under the premise that functional safety is paramount, predicting the service life of rails, especially turnouts, can significantly reduce costs and ensure the safety of railway transportation. This paper understands the evolution of contact fatigue on crossing noses through long-term observation and sampling of crossing noses in turnouts. The authors get images from new to damaged. After image preprocessing, MPI (Magnetic Particle Imaging) is divided into blocks containing local crack information. The obtained local texture information is used for regression prediction using machine-supervised learning and LSTM network (Long Short-Term Memory) methods. Finally, a technique capable of thoroughly evaluating the wear process of crossing noses is proposed.
Coping Mechanisms and Quality of Life of Low-Income Households during the COVID-19 Pandemic: Empirical Evidence from Bangladesh
Authors: Islam Mohammad Mazharul , Islam Mohammad Muzahidul , Khoj Haitham
Published: December 2022

It is well known that uncertainty and various measures implemented by the government, such as lockdown, social distancing, and travel restrictions during the COVID-19 pandemic, severely impacted low-income households in Bangladesh. This situation forced them to put forward various mechanisms to cope with the devastating situation caused by the pandemic. This paper focuses on the impact of the COVID-19 epidemic on the quality of life (QoL) of low-income households, their survival coping mechanisms, and the impact of the coping mechanisms on their QoL. From 1 October 2021 to 30 December 2021, primary data from 1279 households were collected through online and offline surveys from different divisions of Bangladesh, and were used to analyze the income-generation, transfer, and cost-minimization practices adopted by the households during the pandemic. The Statistical Package for Social Science (SPSS) version 25 was utilized for data analysis. We employed multivariate and regression statistical techniques to achieve the study objectives. The investigation found that QoL declined significantly due to the COVID-19 crisis. The findings also confirmed that coping mechanisms adopted by households varied according to demographic characteristics, and the QoL deteriorated significantly more in those households that adopted more coping mechanisms relative to others, regardless of socio-demographic features. The findings emphasize the importance of recording grounded survey data to track and gather information on the QoL of low-income households during the pandemic, and of constructing evidence-based policy responses. Furthermore, the study contributes to enriching the existing literature on the impact of the corona pandemic, and can serve as a source for potential studies. This study contributes to a clearer picture of the effects of COVID-19 trauma. This survey-based empirical study provides an understanding of the initial micro-level effects of COVID-19 in Bangladesh. This study gives a synopsis of the extent to which Bangladeshi households adopted mechanisms to deal with the COVID-19 crisis and the effects of the adoption of these mechanisms on quality of life.
Remediation of the Alluvial Aquifer of the Sardas Landfill (Sabiñánigo, Huesca) by Surfactant Application
Authors: Guadaño Joaquín , Gómez Jorge , Fernández Jesús , Lorenzo David , Domínguez Carmen M. , Cotillas Salvador , García-Cervilla Raúl , Santos Aurora
Published: December 2022

Sardas Landfill at Sabiñánigo Huesca is polluted with Dense Non-Aqueous Liquid Phases (DNAPLs) composed of a complex mixture of chlorinated organic compounds (COCs). This DNAPL was produced as liquid waste from lindane production being dumped decades ago in the unlined landfills close to the lindane factory. This DNAPL migrated by gravity through the subsurface and accumulated in the contact between the alluvial and marls layers (about 15 m b.g.l.). Seven injections of an aqueous emulsion of a biodegradable non-ionic surfactant (E-Mulse 3®) were carried out at the most polluted areas of the Sardas alluvial. Injections were carried out between April and November 2021 using different surfactant concentrations (6.7, 20, 25 and 50 g/L), injection volumes (0.2 to 7 m3) and injection flow rates (0.08–0.85 m3/h). Injected fluids were extracted in the same well or surrounding wells, and the time elapsed between surfactant injection and extraction varied between 24 and 72 h. A total of 22 m3 were injected into the alluvial, and more than double this injected volume was extracted. Injection and extraction points were in the contact between the marls and the alluvial layer. Extracted fluid accumulated in tanks, and phases separated. DNAPL recovered here was mobilized rather than solubilized and managed as toxic waste. The aqueous supernatant was treated in a wastewater treatment plant with physicochemical treatment (including adsorption in activated carbon) before being discharged into the environment. The transport of the injected fluids was monitored by conductivity profiles using bromide (260–538 mg·L−1) as a conservative tracer. High radial dispersion of the injected fluid was found. Surfactant losses by adsorption in the alluvial and absorption in DNAPL were noticed, and both surfactant and contamination did not escape from the capture zone. Monitoring since 2018 of the COCS in groundwater and the DNAPL presence in the contact between alluvial and marls layers showed a significant reduction of COCs in the treated zone with the surfactant injections.
Assessment of Wayfinding Performance in Complex Healthcare Facilities: A Conceptual Framework
Authors: Al-Sharaa Ammar , Adam Mastura , Amer Nordin Amer Siddiq , Mundher Riyadh , Alhasan Ameer
Published: December 2022

Wayfinding is considered to be one of the most demanding challenges to be performed by hospitals’ users. Wayfinding has been an interest among researchers from different fields, such as architecture, interior design, cognitive psychology, and facilities management, to name a few. Previous scholars have highlighted the need for a holistic framework taking into consideration both user and environmental factors. A narrative review of the literature was carried out to understand the full extent of the issue and address the ever-increasing demand for a holistic assessment framework. This article attempts to address the underlying gap by proposing a comprehensive framework that takes into account both facets of the issue through a narrative review of the literature to some of the most prominent research attempts to address the problem of wayfinding in complex healthcare settings. Furthermore, the proposed framework can assist both researchers and practicing professionals by providing a comprehensive understanding of the issue of complex wayfinding as well as of the variables to be investigated in the assessment process.
Evaluation of Children’s Discourses Regarding Imaginary Companion: The Case of Türkiye
Authors: Yazıcı Arıcı Elçin , Keskin Hasan Kağan , Papadakis Stamatios , Kalogiannakis Michail
Published: December 2022

Preschool children’s imaginary companions are a relatively unexplored phenomenon. This article provides information about a qualitative study investigating Turkish children’s statements about their imaginary companions. Forty-six children aged between 48–60 months were interviewed. A phenomenological pattern was used to explore themes in the research. As a result of the research, six themes and 24 categories were created. When the themes were reviewed, it was seen that the children’s imaginary companions were male in terms of gender, clothing, and accessories in terms of appearance characteristics, and happiness in terms of mood characteristics. In addition, considering the thinking status of their imaginary companions, it was determined that they concentrated in the category of entertainment/game, in the category of communication skills in terms of liked/admirable features, and finally in the category of negative behaviour as disliked/unadmirable features. Addressing imaginary companions in children’s lives in different dimensions can contribute to their development.
Sustainable Planning and Design of Ocean City Spatial Forms Based on Space Syntax
Authors: Zhang Longlong , Yuan Jingwen , Kim Chulsoo
Published: December 2022

The form of an ocean city, as a physical space, has an important impact on the city’s social economy, environment, etc. Whether the internal composition of an ocean city is well organized determines whether its form is sustainable and whether it can better carry out a variety of functions. Considering this context, in this study, we adopted the theory of space syntax (SS) to interpret the sustainability of the ocean city form. This was carried out from the perspective of the composition relationship of the internal organization of the ocean city (OC) physical space. We judged whether the composition relationship of internal space could effectively support the sustainable and healthy functioning of different features of ocean cities through the interpretation of SS-related theories. It is extremely hard to give an accurate definition of the form of a sustainable city. At the same time, it is impossible to make conclusions about which urban form is sustainable. However, combined with the concept of sustainable development, we argue that urban forms that continue to facilitate the virtuous cycle of the society, economy, and environment of a given city and also to be highly habitable for urban residents are sustainable. Thus, based on the above viewpoint, the research object and scope in this study only involved the ontology of the physical space form and whether urban physical space could effectively support the sound and sustainable development of three core elements: urban society, the economy, and the environment. This was comprehensively evaluated through our exploration of the form of urban physical space. Here, space syntax was taken as an analytical theoretical and practical tool to summarize the problems that existed in Shenzhen Bay through data analysis, and corresponding development proposals were put forward. The concept and method behind the strategy analysis of the ocean city (OC) design framework based on SS-related theories were presented and applied to practical cases to perform an objective and rational analysis, guide the design of actual projects, and promote ocean city (OC) design in the transition period in a judicious way. In addition, we discuss how design and planning can promote sustainable urban development.
Effects of the Digital Economy on Carbon Emissions in China: A Spatial Durbin Econometric Analysis
Authors: Chang Xuan , Li Jinye
Published: December 2022

Carbon emission reduction is an important issue for sustainable development around the world, and the digital economy is an important driver of carbon emission reduction. Hence, using panel data from 282 Chinese cities collected during 2011–2019, this study empirically explores the impact of the digital economy on carbon emissions based on the spatial Durbin econometric model. The findings show that there is a positive spatial correlation in carbon emissions among regions. That is, the reduction in carbon emissions in one region can lead to a reduction in carbon emissions in neighboring regions. Meanwhile, the digital economy has significant negative local and spillover effects on carbon emissions. However, the spatial-spillover effect of the digital economy on carbon emission reduction has a regional boundary. It is only significant within a range of 750 km and decreases with increasing geographical distance within this range. As China is a major carbon-emitting country, the findings of this study provide empirical strategies for achieving China’s “double carbon” target and have some reference value for other countries’ sustainable-development strategies.
A Study on the Risk Assessment of Water Conservancy Scenic Spot PPP Projects
Authors: Xu Xue , Zhao Min , Li Xiaoya , Song Chao
Published: December 2022

The water conservancy scenic spot is an important part of China’s water ecological civilization construction and is an important way to transform “clear water and green mountains” into “mountains of gold and silver”. The current development of the water conservancy scenic spot is limited by the conditions of capital, management, and technology. The PPP model, as a means of introducing these elements, is an effective way to realize the marketization, characterization, and high-quality development of water conservancy scenic spots. Due to the particularity and complexity of water conservancy scenic spots, the PPP model, and their combination, the risks in water conservancy scenic spot PPP projects are more complicated. Identification and assessment, as well as response, are necessary ways to reduce project risks. In this paper, the risk evaluation index system and the DEMATEL-ANP-FUZZY risk evaluation model of the water conservancy scenic spot PPP project are put forward and, then, the key risk factors, causal relationship between the factors, and risk level of the project are obtained in combination with case analysis. The results show that risks in construction and operation, as well as political and economic risks, are the key risk factors in the water conservancy scenic spot PPP project, and the natural, economic and political risk factors are the main causes of project risk. Risks in construction and operation, as well as organizational and social risks, are the main affected factors. Further analysis shows that the political and economic factors are the key points to focus on when attempting to reduce the project risk, and suggestions are provided, such as improving the legal and regulatory framework, establishing a reasonable risk-sharing and social capital withdrawal mechanism, unblocking social capital participation channels, and strengthening financial support. This could provide a reference for the risk management of water conservancy scenic spot PPP projects.
The Impact of Management Succession on Corporate Social Responsibility of Chinese Family Firms: The Moderating Effects of Managerial Economic Motivations
Authors: Guo Chan
Published: December 2022

Because the establishment of private enterprises has been allowed by the Chinese government since the 1980s, management successions have occurred in a large number of Chinese family firms in recent years. Grounded in upper echelons theory and considering the generational differences between founders and successors, it is expected that the initiation of a within-family succession will lead to significant changes in firms’ CSR strategies. Applying the difference-in-difference method, the results suggest that family firms having initiated successions have better CSR performance relative to those that have not initiated successions and succession firms prior to the initiation of successions. The paper further finds that not all post-succession family firms demonstrate homogeneity in terms of CSR. The impact of succession on firms’ CSR is more pronounced for succession family firms with debt financing plans and politically connected successors. This paper contributes to the manager-effect literature, family firm CSR research and management succession studies, and it is also useful to policy makers of Chinese government.
An Efficient Wireless Sensor Network Based on the ESP-MESH Protocol for Indoor and Outdoor Air Quality Monitoring
Authors: Khan Anwar Ulla , Khan Mohammad Ehtisham , Hasan Mashhood , Zakri Waleed , Alhazmi Waleed , Islam Tarikul
Published: December 2022

The main aim of this work is to establish a sensor MESH network using an ESP-MESH networking protocol with the ESP32 MCU (a Wi-Fi-enabled microcontroller) for indoor and outdoor air quality monitoring in real time. Each sensor node is deployed at a different location on the college campus and includes sensor arrays (CO2, CO, and air quality) interfaced with the ESP32. The ESP-MESH networking protocol is a low-cost, easy-to-implement, medium-range, and low-power option. ESP32 microcontrollers are inexpensive and are used to establish the ESP-MESH network that allows numerous sensor nodes spread over a large physical area to be interconnected under the same wireless network to monitor air quality parameters accurately. The data of different air quality parameters (temperature, humidity, PM2.5, gas concentrations, etc.) is taken (every 2 min) from the indoor and outdoor nodes and continuously monitored for 72 min. A custom time-division multiple-access (TDMA) scheduling scheme for energy efficiency is applied to construct an appropriate transmission schedule that reduces the end-to-end transmission time from the sensor nodes to the router. The performance of the MESH network is estimated in terms of the package loss rate (PLR), package fault rate (PFR), and rate of packet delivery (RPD). The value of the RPD is more than 97%, and the value of the PMR and PER for each active node is less than 1.8%, which is under the limit. The results show that the ESP-MESH network protocol offers a considerably good quality of service, mainly for medium-area networks.