bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Drilling Parameters in Influence Area of Gas–Solid Interaction during Parallel Drilling Hole
Authors: Zhang Fengyan , Wang Haidong
Published: August 2023

Previous studies have established that the selection of gas extraction borehole parameters is crucial for the effectiveness of gas extraction. To more accurately determine the reasonable extraction radius of gas extraction boreholes in the coal seam, this study was based on the actual occurrence conditions of the coal body. A coal-seam gas-seepage model, considering dynamic changes in permeability under gas–solid coupling conditions, was constructed. It was combined with FLAC3D numerical simulations to develop a borehole extraction model closer to the field’s natural needs. The study revealed the influence of borehole diameter and spacing on gas extraction, obtained the radius of effect of borehole extraction, and optimized the gas extraction borehole parameters based on data simulation experiments. Multiple sets of experimental results indicated that the optimal parameters are a borehole diameter of φ = 113 mm and a borehole spacing of 5 m. Applying these parameters in on-site tests at the 14,303 working faces of a particular mine significantly improved gas extraction efficiency, with a 29.7% increase in gas extraction concentration. This verified the accuracy of the simulation results and provides a scientific basis for cost reduction and efficiency enhancement in wellbore mining.
Pulsed Laser Deposition of Carbon-Based Materials: A Focused Review of Methods and Results
Authors: Gaudiuso Rosalba
Published: August 2023

Pulsed Laser Deposition (PLD) is a highly flexible experimental methodology for the growth of thin films of a broad variety of materials, based on the generation of laser-induced plasmas (LIP) with material ablated from a solid target and on the transfer of the ablated material to a substrate. This review is focused on carbon-based materials—specifically, diamond-like carbon (DLC), graphene and carbyne—and will both discuss the influence of the most critical experimental parameters on the obtained materials and present the experimental developments proposed in the recent literature to tailor the properties of the deposited films and optimize the standard PLD technique for production of various carbon-based materials.
Diagenesis and Diagenetic Mineral Control on Reservoir Quality of Tight Sandstones in the Permian He8 Member, Southern Ningwu Basin
Authors: Zhang Pengbao , Tang Shuheng , Lin Donglin , Chen Yanjun , Wang Xiaoxuan , Liu Zhenxing , Han Feng , Lv Peng , Yang Zhoupeng , Guan Xiaoqu , Hu Jiahua , Gao Yan
Published: August 2023

The sandstone reservoirs of the He8 member within the Lower Permian Shihezi Formation are important targets for oil and gas exploration in the southern Ningwu Basin. This study utilized thin-section identification, scanning electron microscopy, and X-ray diffraction analysis to examine the petrological features and reservoir characteristics, and evaluate the impact of the mineral composition and diagenesis type on the porosity of the sandstone reservoir. Additionally, a multiple linear regression prediction model was developed to predict the distribution of promising sandstone reservoirs in the study area. The results of the analysis revealed that the sandstone of the He8 member is mainly composed of feldspathic lithic sandstone, followed by lithic sandstone. The main reservoir type is characterized by secondarily dissolved pores and micropores within kaolinite aggregates. The low porosity (ranging from 0.2% to 10.7%) and permeability indicate that the He8 member is a tight sandstone reservoir. This reservoir has undergone compaction, cementation, and dissolution diagenesis, and is presently in the stage of mesodiagenesis B. The rigid framework of quartz, the dissolution of feldspar grains, and the intergranular pores of kaolinite are significant contributors to reservoir quality and the main drivers of porosity. In this study, a multivariate linear regression model was developed based on the mineral content of quartz, feldspar, carbonate minerals, kaolinite, smectite, and rock fragments, which accurately predicts the porosity of the studied reservoirs. Based on this model, it was predicted that the north of the Jingle South sub-depression contains a favorable reservoir space in the tight sandstone reservoir of the He8 member. The findings of this study hold significant reference value in the quantitative characterization of tight sandstone reservoirs with similar depositional and diagenetic characteristics, and improving the prediction effect of favorable reservoirs.
Connecting the Dots: Occupational Stressors and PTSD Symptoms as Serial Mediators of the Relationship between Fear of COVID-19 and Burnout among Portuguese Police Officers
Authors: Sousa Bárbara , Correia-Santos Patrícia , Costa Patrício , Maia Ângela
Published: August 2023

Police officers are exposed to several operational and organizational stressors that significantly impact on their mental health. The COVID-19 pandemic was a new stressor that further exacerbated existing stressors, highlighting the need for a better understanding of its impact on the mental health of police officers. This study tested the hypothesis that occupational stressors and PTSD are serial mediators of the relationship between fear of COVID-19 and burnout. Two hundred Portuguese police officers completed an online survey that assessed their fear of COVID-19, exposure to operational and organizational stressors, PTSD, and burnout. The results of the serial mediation analysis indicated that not only do occupational stressors act as mediators between fear of COVID-19 and burnout but also that PTSD is a mediator. The findings of this study underscore the need for interventions to reduce the negative impact of operational and organizational stressors on the mental health of police officers. Furthermore, this study highlights the power of police institutions for prevention and intervention with these professionals. By recognizing the specific stressors that contribute to the development of PTSD and burnout, our study provides a foundation for the development of direct interventions that can help to minimize the adverse effects of these stressors
God, Gould, and the Panda’s Thumb
Authors: Dilley Stephen
Published: August 2023

The panda’s thumb argument, championed by the late Stephen Jay Gould, stands as one of the most famous polemics for common ancestry. In this essay, I analyze Gould’s argument in several steps. First, I attempt to reconstruct the argument in both deductive and likelihood formulations. I contend that both versions of the argument rest on a theological claim—namely, that God would not (likely) create or allow a suboptimal panda’s thumb. I then argue that a wide range of people are not rationally obligated to accept this theological claim. Next, I give special attention to the likelihood formulation’s emphasis on a contrastive argument for evolution over special creation. I contend that a great number of people are not rationally obligated to accept this formulation either. I next consider and reply to an objection that Gould never intended the panda argument as an apologetic for evolution (and an attack on special creation) but rather as a critique of adaptationism. Finally, I argue that the panda argument conflicts with Gould’s broader views about the human mind and the relationship between theology and science. I also note along the way that the shortcomings of the panda argument apply to a number of other arguments for evolutionary theory. To be sure, I do not criticize evolution itself or the comprehensive grounds for it. Instead, my primary aims are to analyze the panda argument and suggest that caution is in order about similar arguments as well.
Black Esophagus and Recurrence of Duodenal Ulcers: Two Signs of the Same Pathogenic Pathway? A Case Report
Authors: Balducci Daniele , Quatraccioni Claudia , Daretti Luigi Maria , Montori Michele , Bendia Emanuele , Maroni Luca , Benedetti Antonio
Published: August 2023

Black esophagus or acute esophageal necrosis is characterized by circumferential black discoloration of the distal esophageal mucosa. It is a rare condition with a multifactorial pathogenesis, and its most common clinical presentation is acute upper gastrointestinal bleeding. It usually affects elderly patients with multiple comorbidities and is associated with a high mortality rate. This is a case report of a 90-year-old man with multiple comorbidities, including diabetes mellitus, atrial fibrillation with complete atrioventricular block, and a history of ischemic stroke, who presented to the emergency department for a syncopal episode followed by coffee ground emesis. Thoraco-abdominal computer tomography showed thickening of the distal esophagus and ruled out major complications such as perforation. The following esophagogastroduodenoscopy showed black circumferential necrosis of the mid and distal esophagus. Multiple irregular ulcers with black necrotic areas were also present in the bulb and second duodenal portion. During the hospitalization, the patient was treated with PPI, NPO nutrition, and broad-spectrum antibiotics with benefits. Two months later, the patient returned to the emergency department due to a new episode of hematemesis with endoscopic evidence of esophageal stricture without necrosis and recurrence of duodenal ulcers. After a few days, the patient died due to worsening of the underlying comorbidities. A black esophagus is associated with duodenal ulcers, which may recur and are possibly due to a common ischemic origin. In this case report, we explore the potential link between black esophagus and duodenal ulcers, discussing the underlying mechanisms and relevant literature supporting this association.
A Robust and High-Precision Three-Step Positioning Method for an Airborne SAR Platform
Authors: Tong Wenhao , Yu Anxi , Zhang Keke , Dong Zhen
Published: August 2023

When airborne synthetic aperture radar (SAR) encounters long-time global navigation satellite system (GNSS) denial, the system cannot eliminate inertial navigation system (INS) accumulated drift. Platform positioning technology based on SAR image-matching is one of the important auxiliary navigation methods. This paper proposes a three-step positioning method for an airborne SAR platform, which can achieve the robust and high-precision estimation of platform position and velocity. Firstly, the motion model of the airborne SAR platform is established and a nonlinear overdetermined equation set of SAR Range-Doppler based on the ground-control points set obtained by SAR image-matching is constructed. Then, to overcome the ill-conditioned problem generated by the singular Jacobian matrix when solving the equations directly, a three-step robust and high-precision estimation of platform position and velocity is achieved through singular value decomposition and equation decoupling. Furthermore, the error transfer model of systematic and random platform positioning errors is derived. Finally, a set of semi-physical simulation experiments of airborne SAR is conducted to verify the effectiveness of the positioning method and the accuracy of the error model presented in this paper.
Estimating Plant Nitrogen by Developing an Accurate Correlation between VNIR-Only Vegetation Indexes and the Normalized Difference Nitrogen Index
Authors: Çimtay Yücel
Published: August 2023

Nitrogen is crucial for plant physiology due to the fact that plants consume a significant amount of nitrogen during the development period. Nitrogen supports the root, leaf, stem, branch, shoot and fruit development of plants. At the same time, it also increases flowering. To monitor the vegetation nitrogen concentration, one of the best indicators developed in the literature is the Normalized Difference Nitrogen Index (NDNI), which is based on the usage of the spectral bands of 1510 and 1680 nm from the Short-Wave Infrared (SWIR) region of the electromagnetic spectrum. However, the majority of remote sensing sensors, like cameras and/or satellites, do not have an SWIR sensor due to high costs. Many vegetation indexes, like NDVI, EVI and MNLI, have also been developed in the VNIR region to monitor the greenness and health of the crops. However, these indexes are not very well correlated to the nitrogen content. Therefore, in this study, a novel method is developed which transforms the estimated VNIR band indexes to NDNI by using a regression method between a group of VNIR indexes and NDNI. Training is employed by using VNIR band indexes as the input and NDNI as the output, both of which are calculated from the same location. After training, an overall correlation of 0.93 was achieved. Therefore, by using only VNIR band sensors, it is possible to estimate the nitrogen content of the plant with high accuracy.
Emerging Signal of Englacial Debris on One Clean Surface Glacier Based on High Spatial Resolution Remote Sensing Data in Northeastern Tibetan Plateau
Authors: Wu Yuwei , Zhang Wei , Zhang Shiqiang , Mao Zhonglei , Chen Anan , Li Zhen , Zhang Quan , Guo Zhongming , Jiang Xi , Long Yongqing
Published: August 2023

The Tibetan Plateau contains a large number of mountain glaciers with clean surfaces, where englacial debris is generally entrained by the ice flow and exposed at the glacier margins. The long-term observation on one of the typical clean surface glaciers (the Qiyi Glacier, northern Tibetan Plateau) suggests an early emergence of englacial debris on its transport pathway, with accelerated surface melting from the mid-2000s onwards. Given that the englacial debris layers of the tongue part of Qiyi Glacier are approximately parallel to the glacier surface, the continuing melting might be expected to result in the rapid expansion of exposed debris. Compared with the clean surface ice, debris cover at the same elevation reduced glacier mass loss by ~25.4% during a hydrological year (2020–2021), indicating that the early emergence of englacial debris can protect the glacier from climate warming with prolonged life expectance. As such, future glacial runoff will then reach its peak earlier and be followed by a gentler decreasing trend than model projections with constant clean surface ice. These findings imply that the emerging debris on clean surface glacier may mitigate the glacial-runoff risk, which has so far been neglected in projections of future water supplies.
A Split-Frequency Filter Network for Hyperspectral Image Classification
Authors: Gong Jinfu , Li Fanming , Wang Jian , Yang Zhengye , Ding Xuezhuan
Published: August 2023

The intricate structure of hyperspectral images comprising hundreds of successive spectral bands makes it challenging for conventional approaches to quickly and precisely classify this information. The classification performance of hyperspectral images has substantially improved in the past decade with the emergence of deep-learning-based techniques. Due to convolutional neural networks’(CNNs) excellent feature extraction and modeling, they have become a robust backbone network for hyperspectral image classification. However, CNNs fail to adequately capture the dependency and contextual information of the sequence of spectral properties due to the restrictions inherent in their fundamental network characteristics. We analyzed hyperspectral image classification from a frequency-domain angle to tackle this issue and proposed a split-frequency filter network. It is a simple and effective network architecture that improves the performance of hyperspectral image classification through three critical operations: a split-frequency filter network, a detail-enhancement layer, and a nonlinear unit. Firstly, a split-frequency filtering network captures the interactions between neighboring spectral bands in the frequency domain. The classification performance is then enhanced using a detail-improvement layer with a frequency-domain attention technique. Finally, a nonlinear unit is incorporated into the frequency-domain output layer to expedite training and boost performance. Experiments on various hyperspectral datasets demonstrate that the method outperforms other state-of-art approaches (an overall accuracy(OA) improvement of at least 2%), particularly when the training sample is insufficient.
Rapid Landslide Extraction from High-Resolution Remote Sensing Images Using SHAP-OPT-XGBoost
Authors: Lin Na , Zhang Di , Feng Shanshan , Ding Kai , Tan Libing , Wang Bin , Chen Tao , Li Weile , Dai Xiaoai , Pan Jianping , Tang Feifei
Published: August 2023

Landslides, the second largest geological hazard after earthquakes, result in significant loss of life and property. Extracting landslide information quickly and accurately is the basis of landslide disaster prevention. Fengjie County, Chongqing, China, is a typical landslide-prone area in the Three Gorges Reservoir Area. In this study, we newly integrate Shapley Additive Explanation (SHAP) and Optuna (OPT) hyperparameter tuning into four basic machine learning algorithms: Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Additive Boosting (AdaBoost). We construct four new models (SHAP-OPT-GBDT, SHAP-OPT-XGBoost, SHAP-OPT-LightGBM, and SHAP-OPT-AdaBoost) and apply the four new models to landslide extraction for the first time. Firstly, high-resolution remote sensing images were preprocessed, landslide and non-landslide samples were constructed, and an initial feature set with 48 features was built. Secondly, SHAP was used to select features with significant contributions, and the important features were selected. Finally, Optuna, the Bayesian optimization technique, was utilized to automatically select the basic models’ best hyperparameters. The experimental results show that the accuracy (ACC) of these four SHAP-OPT models was above 92% and the training time was less than 1.3 s using mediocre computational hardware. Furthermore, SHAP-OPT-XGBoost achieved the highest accuracy (96.26%). Landslide distribution information in Fengjie County from 2013 to 2020 can be extracted by SHAP-OPT-XGBoost accurately and quickly.
Retrieving Sub-Canopy Terrain from ICESat-2 Data Based on the RNR-DCM Filtering and Erroneous Ground Photons Correction Approach
Authors: Wu Yang , Zhao Rong , Hu Qing , Zhang Yujia , Zhang Kun
Published: August 2023

Currently, the new space-based laser altimetry mission, Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), is widely used to obtain terrain information. Photon cloud filtering is a crucial step toward retrieving sub-canopy terrain. However, an unsuccessful photon cloud filtering performance weakens the retrieval of sub-canopy terrain. In addition, sub-canopy terrain retrieval would not be accurate in densely forested areas due to existing sparse ground photons. This paper proposes a photon cloud filtering method and a ground photon extraction method to accurately retrieve sub-canopy terrain from ICESat-2 data. First, signal photon cloud data were derived from ICESat-2 data using the proposed photon cloud filtering method. Second, ground photons were extracted based on a specific percentile range of elevation. Third, erroneous ground photons were identified and corrected to obtain accurate sub-canopy terrain results, assuming that the terrain in the local area with accurate ground photons was continuous and therefore could be fitted appropriately through a straight line. Then, the signal photon cloud data obtained by the proposed method were compared with the reference signal photon cloud data. The results demonstrate that the overall accuracy of the signal photon identification achieved by the proposed filtering method exceeded 96.1% in the study areas. The sub-canopy terrain retrieved by the proposed sub-canopy terrain retrieval method was compared with the airborne LiDAR terrain measurements. The root-mean-squared error (RMSE) values in the two study areas were 1.28 m and 1.19 m, while the corresponding R2 (coefficient of determination) values were 0.999 and 0.999, respectively. We also identified and corrected erroneous ground photons with an RMSE lower than 2.079 m in densely forested areas. Therefore, the results of this study can be used to improve the accuracy of sub-canopy terrain retrieval, thus pioneering the application of ICESat-2 data, such as the generation of global sub-canopy terrain products.
A Miniaturized Tri-Band Implantable Antenna for ISM/WMTS/Lower UWB/Wi-Fi Frequencies
Authors: Gupta Anupma , Kumar Vipan , Bansal Shonak , Alsharif Mohammed H. , Jahid Abu , Cho Ho-Shin
Published: August 2023

This study aims to design a compact antenna structure suitable for implantable devices, with a broad frequency range covering various bands such as the Industrial Scientific and Medical band (868–868.6 MHz, 902–928 MHz, 5.725–5.875 GHz), the Wireless Medical Telemetry Service (WMTS) band, a subset of the unlicensed 3.5–4.5 GHz ultra-wideband (UWB) that is free of interference, and various Wi-Fi spectra (3.6 GHz, 4.9 GHz, 5 GHz, 5.9 GHz, 6 GHz). The antenna supports both low and high frequencies for efficient data transfer and is compatible with various communication technologies. The antenna features an asynchronous-meandered radiator, a parasitic patch, and an open-ended square ring-shaped ground plane. The antenna is deployed deep inside the muscle layer of a rectangular phantom below the skin and fat layer at a depth of 7 mm for numerical simulation. Furthermore, the antenna is deployed in a cylindrical phantom and bent to check the suitability for different organs. A prototype of the antenna is created, and its reflection coefficient and radiation patterns are measured in fresh pork tissue. The proposed antenna is considered a suitable candidate for implantable technology compared to other designs reported in the literature. It can be observed that the proposed antenna in this study has the smallest volume (75 mm3) and widest bandwidth (181.8% for 0.86 GHz, 9.58% for 1.43 GHz, and 285.7% for the UWB subset and Wi-Fi). It also has the highest gain (−26 dBi for ISM, −14 dBi for WMTS, and −14.2 dBi for UWB subset and Wi-Fi) compared to other antennas in the literature. In addition, the SAR values for the proposed antenna are well below the safety limits prescribed by IEEE Std C95.1-1999, with SAR values of 0.409 W/Kg for 0.8 GHz, 0.534 W/Kg for 1.43 GHz, 0.529 W/Kg for 3.5 GHz, and 0.665 W/Kg for 5.5 GHz when the applied input power is 10 mW. Overall, the proposed antenna in this study demonstrates superior performance compared to existing tri-band implantable antennas in terms of size, bandwidth, gain, and SAR values.
Cyclic Generative Attention-Adversarial Network for Low-Light Image Enhancement
Authors: Zhen Tong , Peng Daxin , Li Zhihui
Published: August 2023

Images captured under complex conditions frequently have low quality, and image performance obtained under low-light conditions is poor and does not satisfy subsequent engineering processing. The goal of low-light image enhancement is to restore low-light images to normal illumination levels. Although many methods have emerged in this field, they are inadequate for dealing with noise, color deviation, and exposure issues. To address these issues, we present CGAAN, a new unsupervised generative adversarial network that combines a new attention module and a new normalization function based on cycle generative adversarial networks and employs a global–local discriminator trained with unpaired low-light and normal-light images and stylized region loss. Our attention generates feature maps via global and average pooling, and the weights of different feature maps are calculated by multiplying learnable parameters and feature maps in the appropriate order. These weights indicate the significance of corresponding features. Specifically, our attention is a feature map attention mechanism that improves the network’s feature-extraction ability by distinguishing the normal light domain from the low-light domain to obtain an attention map to solve the color bias and exposure problems. The style region loss guides the network to more effectively eliminate the effects of noise. The new normalization function we present preserves more semantic information while normalizing the image, which can guide the model to recover more details and improve image quality even further. The experimental results demonstrate that the proposed method can produce good results that are useful for practical applications.
Neural-Network-Based Localization Method for Wi-Fi Fingerprint Indoor Localization
Authors: Zhu Hui , Cheng Li , Li Xuan , Yuan Haiwen
Published: August 2023

Despite the high demand for Internet location service applications, Wi-Fi indoor localization often suffers from time- and labor-intensive data collection processes. This study proposes a novel indoor localization model that utilizes fingerprinting technology based on a convolutional neural network to address this issue. The aim is to enhance Wi-Fi indoor localization by streamlining the data collection process. The proposed indoor localization model leverages a 3D ray-tracing technique to simulate the wireless received signal strength intensity (RSSI) across the field. By incorporating this advanced technique, the model aims to improve the accuracy and efficiency of Wi-Fi indoor localization. In addition, an RSSI heatmap fingerprint dataset generated from the ray-tracing simulation is trained on the proposed indoor localization model. To optimize and evaluate the model’s performance in real-world scenarios, experiments were conducted using simulated datasets obtained from the publicly available databases of UJIIndoorLoc and Wireless InSite. The results show that the new approach solves the problem of resource limitation while achieving a verification accuracy of up to 99.09%.
Research on Mechanical Equipment Fault Diagnosis Method Based on Deep Learning and Information Fusion
Authors: Jiang Dongnian , Wang Zhixuan
Published: August 2023

Solving the problem of the transmission of mechanical equipment is complicated, and the interconnection between equipment components in a complex industrial environment can easily lead to faults. A multi-scale-sensor information fusion method is proposed, overcoming the shortcomings of fault diagnosis methods based on the analysis of one signal, in terms of diagnosis accuracy and efficiency. First, different sizes of convolution kernels are applied to extract multi-scale features from original signals using a multi-scale one-dimensional convolutional neural network (1DCNN); this not only improves the learning ability of the features but also enables the fine characterization of the features. Then, using Dempster–Shafer (DS) evidence theory, improved by multi-sensor information fusion strategy, the feature signals extracted by the multi-scale 1DCNN are fused to realize the fault detection and location. Finally, the experimental results of fault detection on a flash furnace show that the accuracy of the proposed method is more than 99.65% and has better fault diagnosis, which proves the feasibility and effectiveness of the proposed method.
Enhanced Adsorption of Chromate and Arsenate Ions from Contaminated Water with Emphasis on Polyethylenimine Modified Materials: A Review
Authors: Xanthopoulou Maria , Katsoyiannis Ioannis A.
Published: August 2023

Heavy metals in water pose a great threat to human health, and water treatment remains a critical issue globally. Among various water treatment techniques, adsorption has been proven to be an excellent way to remove heavy metals from water due to its advantages, like low cost, availability, profitability, ease of operation, and efficiency. Heavy metals such as chromium and arsenic are present in water in the form of anions, while many common adsorbents, such as biochar and activated carbons, cellulose, chitosan, clays, and silica, tend to acquire a negative surface charge. The surface charge of the adsorbent plays a major role in its interaction with heavy metal ions. Polyethylenimine is a polymer with a high cationic charge density. Modification of these adsorbents with polyethylenimine results in higher selectivity for these anions. The adsorption capacity is related to the efficiency of the introduction of polyethylenimine, which depends on the surface properties of the adsorbent. This review focuses on the effect of modification with polyethylenimine on the adsorption capacity of common adsorbents for the removal of heavy metal ions, such as chromate and arsenate, from water.
Drivers’ Experiences and Informed Opinions of Presence Sensitive Lighting Point towards the Feasibility of Introducing Adaptive Lighting in Roadway Contexts
Authors: Pihlajaniemi Henrika , Luusua Aale , Juntunen Eveliina
Published: August 2023

Applications of adaptive and intelligent lighting technologies such as presence sensitive lighting, potentially offer solutions for reducing the energy consumption of road lighting while maintaining user comfort and safety. However, little is known about road users’ experiences of such lighting. To address this gap, we conducted a real-world case study of a presence sensitive roadway lighting on a collector road in a housing area in southern Finland. New, controllable LED lighting with PIR (passive infrared) presence sensors was implemented along the road, and test scenarios were designed, programmed, and tested. The lighting was adapted both to motor vehicles using the road and to the measured traffic density along it. Drivers’ experiences and attitudes toward the lighting were collected in a three-phase evaluation with questionnaires from the community of about 1000 households using the road as part of their daily mobility. The results indicate that as an experience, presence sensitive lighting in a road environment was at least as positive as traditional, uncontrolled lighting. User experiences of presence sensitive lighting did not differ from the experiences of uncontrolled lighting regarding pleasantness, uniformity, glare, and road visibility. Most of the drivers (86%) did not notice any dynamic change in the lighting. When informed about the tested lighting strategies, most of the participants (72%) would prefer either one of the intelligent lighting modes to be the permanent lighting solution. The results of this exploratory, real-world study point towards the potential feasibility of this technology from a user experience perspective, as the experienced stability of the lighting was unaltered in the tested scenarios; importantly, it also highlights the need to study adaptive roadway lighting further, especially through confirmatory studies in controlled settings.
Simulation of Lead-Free Heterojunction CsGeI2Br/CsGeI3-Based Perovskite Solar Cell Using SCAPS-1D
Authors: Kenfack Abraham Dimitri Kapim , Thantsha Nicolas Matome , Msimanga Mandla
Published: August 2023

This paper presents the simulation of the novel prototype of a heterojunction perovskite solar cell (PSC) based on CSGeI2Br/CSGeI3. The device consists of two absorber layers (CSGeI2Br, CSGeI3), an electron transport layer (ETL) chosen as TiO2 and a hole transport layer (HTL) given as poly(3-hexylthiophene) (P3HT). Within the simulation, the effects of thickness, doping and defect density in each absorber layer and different back contact metal electrodes on electrical parameters (efficiency, short circuit current, open circuit voltage, and fill factor) are evaluated. In addition, the contribution of the HTL (doping density and thickness), temperature, shunt and series resistance were also checked on the same electrical parameters. The simulations are conducted in standard test conditions with the irradiation normalized as 0.1 W/cm2 using the SCAPS-1D platform. The maximum efficiency obtained within the simulation of this device was about 31.86%. For this device, the thickness of the CSGeI3 layer should be around 900 nm, while that of the CsGeI2Br should be around 100 nm to facilitate optimal absorption of the incident photons. The doping density in the absorber layer is such that in CsGeI3 should be around 1018 cm−3 and around 1016 cm−3 in the CsGeI2Brlayer. The defects densities in both layers of the perovskite materials should be around 1014 cm−3. Concerning the HTL, the thickness and the doping density of the P3HT should be around 50 nm and  1018 cm−3, respectively. In terms of the back contact electrode, the work function of the metal should be at least equal to 5 eV, corresponding to gold (Au) metal. The series resistance due to the connection of the cell to the external load should be very small, while the shunt resistance due to the leakage current in the solar cell should be high. Furthermore, the operating temperature of the new PSC should be maintained at an ambient level of around 25 °C in order to deliver high efficiency.
Urban Planning and Green Landscape Management Drive Plant Diversity in Five Tropical Cities in China
Authors: Cui Jianpeng , Zhu Meihui , Guo Linyuan , Zhang Haili , Hughes Alice C. , Wang Huafeng
Published: August 2023

Green space is essential in urban areas to maintain, and improve human well-being. To better understand the impact of environmental and socioeconomic changes on the sustainability of tropical urban green space landscapes, work is needed to explore the patterns of plant diversity and its drivers in urban green spaces. We explore urban floristic diversity patterns based on samples from 826 urban functional units located in five cities in the tropical coastal region of China. Field surveys were conducted to obtain data on plant diversity, land use types, socioeconomic characteristics, and environmental characteristics within these units. Plant diversity within the cities varied significantly among land-use types, with high-rise housing, parks, and universities exhibiting higher diversity. The diversity of cultivated plant species and the regional economy showed a significant positive correlation (β coefficient = 0.15, p-value < 0.05), while an increase in the diversity of spontaneously growing plant species and native species was linked to building age (β coefficient = 0.12, p-value < 0.01; β coefficient = 0.13, p-value < 0.01). Management also affected plant species diversity, with watering and maintenance frequency having a positive association. Urban plant diversity patterns result from a combination of multiple factors, and different drivers affect native vs. non-native plant diversity Socio-economic factors are the primary driver of urban plant diversity patterns, as space management and maintenance determine what can grow in different areas. This study has important practical significance for policymakers and managers in developing and managing urban green spaces more sustainably.
Review of Crisis Management Frameworks in Tourism and Hospitality: A Meta-Analysis Approach
Authors: Casal-Ribeiro Mariana , Boavida-Portugal Inês , Peres Rita , Seabra Cláudia
Published: August 2023

Given the global impact of COVID-19 (SARS-CoV-2) on the tourism industry, crisis management has once again become a hot topic for research. This article reviews the state of the art in the existing literature on crisis management frameworks in tourism and hospitality through a meta-analysis approach. A total of 36 articles published in peer-reviewed journals between January 2000 and December 2022 were included in this review. The articles covered perspectives of different crisis events, including natural disasters, conflicts, weather-related events and pandemics. The findings show 14 key crisis management frameworks developed in past literature. These findings are critically reviewed, analysing their core concepts in each stage and highlighting their common elements and differentiating components. The study also recognizes the relevance of adopting a multi-perspective approach and proactive planning in crisis management for destinations and tourism organizations to achieve long-term resilience. Lastly, suggestions and directions for future research in this research field are pointed out.
A Study on the Intention of Shanghai Residents to Travel Abroad in the Post-Pandemic Era Based on the Theory of Planned Behavior
Authors: Hu Anan , Li Houqi , Pang Jinyuan , Zhang Huanfei
Published: August 2023

This study has adopted the theory of planned behavior as a framework to examine the relationship among subjective norms, perceived behavioral control, perceived policy orientation, perceived pandemic response capabilities, attitudes, and behavioral intentions towards outbound travel in a post-pandemic society. Specifically, a total of 895 valid questionnaires were employed to test the 9 hypotheses proposed in this study. The results of the structural equation modeling (SEM) analysis show that subjective norms, perceived behavioral control, and perceived policy orientation positively impact residents’ intention to travel abroad. Furthermore, attitude partially mediates the relationship between subjective norms, perceived behavioral control, perceived policy orientation, and residents’ intention to travel abroad. However, the study indicates that the impact of perceived pandemic response capabilities on residents’ intention to travel abroad is not significant. This study’s conclusions emphasize that external policy factors can significantly influence tourists’ intention to travel abroad, contributing to the theoretical research on consumer outbound tourism behavior. Moreover, the study provides important implications for the policy formulation of outbound tourism enterprises and destination governments.
Intercropping Perennial Fruit Trees and Annual Field Crops with Aromatic and Medicinal Plants (MAPs) in the Mediterranean Basin
Authors: Marotti Ilaria , Whittaker Anne , Bağdat Reyhan Bahtiyarca , Akin Pervin Ari , Ergün Namuk , Dinelli Giovanni
Published: August 2023

The Mediterranean basin (MB), a “climate hotspot”, is experiencing faster than average increases in global temperature and water deficit, as well as soil degradation, with detrimental impacts on food crop yield and pest/pathogen incidence. Hence, there is an urgent requisite for sustainable crop diversification strategies to promote crop resilience, soil quality conservation and pest/pathogen control. Intercropping is a strategy that has yet to be widely adopted. Presently, cereal–legume combinations represent the most common intercrops. Of relevance, a large number of medicinal and aromatic plants (MAPs), native to the MB, serve as potentially profitable indigenous resources for intercropping with food crops. Environmentally sustainable benefits of MB MAP intercropping with food crops have ironically been reported largely from research outside the MB. The present study aims to review the published literature from 2003 to 2023 on MAP intercropping with perennial nut/fruit crops and annual field crops in the MB. Published research is scarce but shows a promising upward trend, with 70% and 47% of intercropping studies with perennials and annual field crops, respectively, dated between 2020 and 2023. MAP intercropping shows potential in augmenting yield, pest/pathogen and weed control, soil health and cash crop quality, warranting further research with more widespread adoption in the MB.
A Non-Isolated High Voltage Gain DC–DC Converter Suitable for Sustainable Energy Systems
Authors: Alghaythi Mamdouh L.
Published: August 2023

A non-isolated high gain DC–DC converter with magnetic coupling and a VM circuit is proposed in this study. By the use of the appropriate coupled inductor turn ratio, the output voltage of the recommended topology can be raised. The VM circuit is used to boost the voltage gain even further as well as to clamp the voltage spike across the switch, which results in a lower voltage on the switch. As a result, a MOSFET switch with a lower ON-state resistance (RDS-ON) is used which, in turn, causes the conduction losses to be reduced and the entire system efficiency to be raised. Another advantage of the proposed structure is the ZCS of the diodes, which reduces the voltage drop losses caused by the regenerative diodes. The function modes analysis and the theoretical equations are accomplished. A comparison survey with other prior works is being developed to investigate the competency of the proposed converter. Based on this, the higher voltage gain and efficiency as well as the lower voltage stress on the semiconductors can be achieved by the proposed converter compared to the other converters. The effectiveness of the proposed converter is confirmed by the experimental results at a laboratory-scale operating under 150 V output voltage with a 96% efficiency at the 150 W full load and a 25 kHz switching frequency.
Synthesis and Characterization of a Quercetin-Based Nanocomposite and Its Ameliorating Impacts on the Growth, Physiological, and Biochemical Parameters of Ocimum basilicum L. under Salinity Stress
Authors: Arshneshin Homa , Salimi Azam , Razavi Seyed Mehdi , Khoshkam Maryam
Published: August 2023

Quercetin (Qu), as an essential flavonoid in plants with antioxidant properties, scavenges environmental stress-induced ROS. Quercetin-based nanocomposites (QNCs) with the same and adequate properties were designed and synthesized for effective Qu delivery in Ocimum basilicum. QNCs were synthesized using the coacervation method, and their effect on the growth, physiological, biochemical, and phytochemical traits of O. basilicum under salinity stress was investigated. Various treatments, including selected concentrations of Qu (0.01 mg/mL) and QNCs (0.01 mg/mL), and four concentrations of NaCl (0, 50, 100, 150 mM) at the vegetative stages, were applied. Results showed that stress markers (Electrolyte leakage, malondialdehyde, hydrogen peroxide) increased with increasing salinity levels. Conversely, salinized plants showed a reduction in plant growth parameters (seed germination, root and shoot length, fresh and dry weight of shoot and root, and plant height) and physiological and photosynthetic parameters (Relative water content, photosynthesis rate, stomatal conductance, photosynthetic pigments, and chlorophyll fluorescence), while application of Qu and QNCs increased these critical parameters. Furthermore, Qu and QNCs enhanced O. basilicum’s tolerance to salinity by increasing compatible solutes content such as glycine betaine, proline, total free amino acids, and soluble carbohydrates; increasing antioxidant enzyme activity; increasing antioxidants content like anthocyanins, tannins, phenols, and flavonoids; and decreasing proteins content and stress markers in plant tissues. Our study suggests that treatment with Qu and QNCs is an effective strategy that can be used to enhance the salt tolerance of O. basilicum plants, and QNCs treatment had a better effect than treatment with Qu.
Extraction of Fish Protein Concentrates from Discards and Combined Application with Gelatin for the Development of Biodegradable Food Packaging
Authors: Athanasopoulou Evmorfia , Michailidi Anna , Ladakis Dimitrios , Kalliampakou Katerina I. , Flemetakis Emmanouil , Koutinas Apostolis , Tsironi Theofania
Published: August 2023

Fish waste accounts for almost one-third of the total fish production annually. The main objective of this study was to upcycle fish by-products to produce biodegradable packaging materials. Fish protein concentrate (FPC) was extracted from gilthead seabream by-catch (flesh and skin). FPC (3%) and gelatin (3%) were used to produce film-forming solutions. The films were produced according to the solvent casting method. The produced films were tested as packaging materials via the determination of different film properties. The wettability of the packaging materials was characterized based on the determination of the contact angle. Water vapor permeability was evaluated using the ASTM E96/E96M standardized method. The evaluation of mechanical properties was based on the Young’s modulus, tensile strength, and elongation at break. Color was measured using a CIELab system. The incorporation of FPC into the produced membranes resulted in a reduced contact angle from 108.5° to 90.6°; however, both films were characterized as hydrophobic materials. Films supplemented with FPC had lower tensile strength values compared to pure gelatin films, but higher elongation values without statistically significant differences. The color parameters (L,a,b) indicated that gelatin films and FPC–gelatin films were colorless and transparent (L > 90), an important parameter for food packaging materials. The production of biodegradable packaging materials from FPC and gelatin may effectively reduce petroleum-based plastics under the circular economy model.
Thermal and CFD Analyses of Sustainable Heat Storage-Based Passive Greenhouse Dryer Operating in No-Load Condition
Authors: Ahmad Asim , Prakash Om , Sarangi Shailesh Kumar , Singh Chauhan Prashant , Chatterjee Rajeshwari , Sharma Shubham , Kumar Raman , Tag Sayed M. , Kumar Abhinav , Salah Bashir , Ullah Syed Sajid
Published: August 2023

This article presents a comprehensive study on thermal and computational fluid dynamics (CFD) analysis of an innovative greenhouse dryer designed for passive operation under a no-load condition. The dryer incorporates hybrid thermal storage at the floor and a reflective mirror with thermocoal as the north wall, transforming a classical even-span greenhouse dryer into an efficient and effective system. The experimentation was conducted under clear sky conditions, with variations in global solar radiation (GSR) ranging from 166.6 to 1209 W/m2, resulting in an average value of 875.9 W/m2. The variations in GSR influenced other ambient parameters, including ambient temperature (28.7 °C to 35.6 °C), ambient relative humidity (33.2% to 45.7%), and ambient wind speed (0.1 to 1.02 m/s). Indoor parameters of the proposed dryer, such as inside temperature (31 °C to 47.35 °C), inside relative humidity (31.1% to 39.1%), ground temperature (44.2 °C to 70.6 °C), and outlet temperature (29 °C to 45.35 °C), were measured hourly. The average values of these parameters were 41.25 °C, 35.31%, 61.65 °C, and 39.25 °C, respectively. Quantitative parameters, including heat loss, overall heat transfer coefficient, coefficient of diffusion, and instantaneous efficiency, were calculated to evaluate the dryer’s performance. The proposed dryer exhibited an improved range of overall heat transfer coefficients (3.87 to 5.03 W/m2 K) compared to the modified greenhouse dryer under passive mode and the conventional greenhouse under passive mode. CFD analysis provided temperature distribution plots showing a progressively increasing range of temperatures near the trays, ranging from 310 K to 335 K, suitable for natural convection drying. The findings highlight the superior performance of the innovative dryer compared to contemporary systems. This research contributes to the advancement of drying technology and holds potential for applications in the agriculture and food processing industries.