bluuebunny/crossref_metadata_2025 huggingface dataset:
Drug Safety and Suicidality Risk of Chronic Pain Medications
Authors: Syed Osman , Jancic Predrag , Fink Adam B. , Knezevic Nebojsa Nick
Published: October 2023

Chronic pain is one of the main leading causes of disability in the world at present. A variety in the symptomatology, intensity and duration of this phenomenon has led to an ever-increasing demand of pharmacological treatment and relief. This demand for medication, ranging from well-known groups, such as antidepressants and benzodiazepines, to more novel drugs, was followed by a rise in safety concerns of such treatment options. The validity, frequency, and diversity of such concerns are discussed in this paper, as well as their possible effect on future prescription practices. A specific caution is provided towards the psychological safety and toll of these medications, regarding suicidality and suicidal ideation. Most significantly, this paper highlights the importance of pharmacovigilance and underscores the necessity of surveillance programs when considering chronic pain medication.
Calculation of BaGa4Se7 OPO/OPA Output Spectrum Characteristics
Authors: Liu Yu , Wan Tianjian , Li Zhiyong , Zhu Ziren , Bai Jinzhou , Tian Juntao , Wang Hai , Lu Yue , Su Xinjun , Tan Rongqing , Ke Changjun , Zheng Yijun
Published: October 2023

Optical parametric oscillation (OPO) or optical parametric amplification (OPA) systems offer significant potential for generating high-energy, narrow-pulse laser output, finding applications across various domains. To achieve efficient amplification in cascade with amplifiers, precise frequency domain matching between OPO/OPA systems and amplifiers is imperative. Therefore, preliminary simulation and computation of the spectral characteristics of OPO/OPA systems are of paramount importance in the early stages of experimentation. Currently, the calculation of OPO/OPA output spectrum characteristics is limited to estimating the influence of pump light characteristics on output spectrum linewidth, a consideration that remains incomplete. This paper presents a comprehensive computational approach that takes into account the impact of four crucial factors on the output spectrum characteristics: pump light linewidth, pump light divergence angle, the walk-off effect, and the absorption loss of the crystal. This method finely characterizes the features of the output spectrum. The results obtained through the proposed approach align well with experimental results, underscoring its effectiveness. This study aims to obtain the output spectrum characteristics of BaGa4Se7 OPO/OPA through calculations to provide theoretical guidance for subsequent cascade amplification experiments.
Manipulation of Population Levels through Zeno-Type Measurements
Authors: Contreras Sánchez Javier , Castillo-Alvarado Fray de Landa , Hernández-Pozos José Luis
Published: October 2023

We present a scheme, based on Bloch equations and Zeno-type measurements, that allows the control of the probability density evolution of the eigenstates of a V-type system. The equations are solved numerically and we present how the population in each level can be controlled using different sequences of “pulse measurements”. The entropy between the “measurement device” and the field used to perform the measurement process is evaluated for different strengths of such field, these calculations show that the entropy is maximized when we are in the Zeno regime. The results shown here unveil different possible strategies for controlling the population levels of a V-type system and could be implemented, for example, in trapped ions or RMN qubits.
A Simple and Effective Method to Enhance the Mechanical Properties, Dimensional Stability, and Mildew Resistance of Bamboo Scrimber
Authors: Xu Jiayu , Zhou Zhezhe , Zhang Xiaochun , Xu Yantao
Published: October 2023

Given the increasingly prominent contradiction between the supply of and demand for wood, the abundant resource of bamboo can be a good substitute. Bamboo scrimber can effectively improve the utilization rate of bamboo and has good mechanical properties. However, bamboo scrimber has the problem of poor mildew resistance, and does not meet the requirements for outdoor applications. In this study, in order to further improve the mildew resistance and mechanical properties of bamboo scrimber, alkali treatment was used to remove some nutrients from the bamboo bundles and change the pH of the bamboo scrimber. The results showed that nutrients such as hemicellulose, lignin, starch, and sugar were notably removed from bamboo bundles, and the pH of bamboo was slightly alkaline. The anti-mildew effect was significantly enhanced, which could allow use in outdoor environments, and the mechanical properties and dimensional stability were also improved. Among them, TB6 bamboo scrimber showed comprehensively excellent properties. The infection time in the laboratory mildew test increased from 3 days to more than 30 days, and the infection time in the outdoor mildew resistance test increased from 1 week to more than 8 weeks; the static bending intensity of TB6 increased by 62.6% to 150 MPa, and the bending modulus increased by 71.7% to 14.2 GPa; the change rate of water absorption thickness was reduced to 0.58%. This modification method effectively improved the mildew resistance of bamboo scrimber, while maintaining high mechanical strength, and provides a new method for the outdoor application of bamboo scrimber.
Degradation of Mechanical Properties of A-PET Films after UV Aging
Authors: Vasylius Marius , Tadžijevas Artūras , Šapalas Deivydas , Kartašovas Valentinas , Janutėnienė Jolanta , Mažeika Pranas
Published: October 2023

In 2018, the European Commission adopted the European Strategy for Plastics in a Circular Economy, which outlines key actions to reduce the negative impact of plastic pollution. The strategy aims to expand plastic recycling capacity and increase the proportion of recycled materials in plastic products and packaging. Using recycled plastic can save 50–60% energy compared to virgin plastic. Recycled PET can be used in the production of A-PET films, which are predominantly used in thermo-vacuum forming for food packaging. Storage conditions can influence the mechanical properties of polymer materials. This work presents changes in the mechanical properties of A-PET films after UV irradiation. An experimental investigation of the UV aging of A-PET films was conducted in a UV aging chamber. The specimens were exposed to a UV radiation dose rate of 2.45 W/m2 for 1, 2, 4, 8, 16, 24, 32, and 40 h. UV measurements were also taken on a sunny day to compare the acceleration of UV irradiation in the UV aging chamber. Mechanical tensile tests were performed on two different three-layer A-PET films (100% virgin and 50% recycled). The tensile strength and relative elongation of the A-PET films were determined, and the work required to break the film was calculated. The total consumed work was divided into the work needed for elastic and plastic deformations. A study of the UV aging of A-PET films confirmed a significant effect on the films, including a loss of plasticity even after brief exposure to solar irradiance. The results of the puncture impact test further confirmed the deterioration of the mechanical properties of A-PET material due to exposure to UV radiation, with a greater effect observed for the recycled material.
Sustainable Polyhydroxyalkanoate Production from Food Waste via Bacillus mycoides ICRI89: Enhanced 3D Printing with Poly (Methyl Methacrylate) Blend
Authors: Rofeal Marian , Abdelmalek Fady , Pietrasik Joanna
Published: October 2023

In view of implementing green technologies for bioplastic turning polices, novel durable feedstock for Bacillus mycoides ICRI89 used for efficient polyhydroxybutyrate (PHB) generation is proposed herein. First, two food waste (FW) pretreatment methods were compared, where the ultrasonication approach for 7 min was effective in easing the following enzymatic action. After treatment with a mixture of cellulase/amylases, an impressive 25.3 ± 0.22 g/L of glucose was liberated per 50 g of FW. Furthermore, a notable 2.11 ± 0.06 g/L PHB and 3.56 ± 0.11 g/L cell dry eight (CDW) over 120 h were generated, representing a productivity percentage of 59.3 wt% using 25% FW hydrolysate. The blend of polyhydroxybutyrate/poly (methyl methacrylate) (PHB/PMMA = 1:2) possessed the most satisfactory mechanical properties. For the first time, PHB was chemically crosslinked with PMMA using dicumyl peroxide (DCP), where a concentration of 0.3 wt% had a considerable effect on increasing the mechanical stability of the blend. FTIR analysis confirmed the molecular interaction between PHB and PMMA showing a modest expansion of the C=O stretching vibration at 1725 cm−1. The DCP-PHB/PMMA blend had significant thermal stability and biodegradation profiles comparable to those of the main constituent polymers. More importantly, a 3-Dimetional (3D) filament was successfully extruded with a diameter of 1.75 mm, where no blockages or air bubbles were noticed via SEM. A new PHB/PMMA “key of life” 3D model has been printed with a filling percentage of 60% and a short printing time of 19.2 min. To conclude, high-performance polymeric 3D models have been fabricated to meet the pressing demands for future applications of sustainable polymers.
A Database Extension for a Safety Evaluation of a Hydrogen Refueling Station with a Barrier Using a CFD Analysis and a Machine Learning Method
Authors: Kang Hyung-Seok , Hwang Ji-Won , Yu Chul-Hee
Published: October 2023

A methodology is proposed to extend datasets in a database suitable for use as a reference tool to support an evaluation of damage mitigation by a barrier wall in a hydrogen refueling station (HRS) during a vapor cloud explosion (VCE) accident. This is realized with a computational fluid dynamic (CFD) analysis and machine learning (ML) technology because measured data from hydrogen explosion tests with various installed barrier models usually require considerable amounts of time, a secured space, and precise measurements. A CFD sensitivity calculation was conducted using the radXiFoam v1.0 code and the established analysis methodology with an error range of approximately ±30% while changing the barrier height from that was used in an experiment conducted by the Stanford Research Institute (SRI) to investigate the effect of the barrier height on the reduction in peak overpressures from an explosion site to far fields in an open space. The radXiFoam code was developed based on the open-source CFD software OpenFOAM-v2112 to simulate a VCE accident in a humid air environment at a compressed gaseous or liquefied HRS. We attempted to extend the number of datasets in the VCE database through the use of the ML method on the basis of pressure data predicted by a CFD sensitivity calculation, also uncovering the possibility of utilizing the ML method to extend the VCE database. The data produced by the CFD sensitivity calculation and the ML method will be examined to confirm their validity and applicability to hypothetical VCE accident simulations if the related test data can be produced during experimental research. The database constructed using core data from the experiment and extended data from the CFD analysis and the ML method will be used to increase the credibility of radXiFoam analysis results for VCE accident scenarios at HRSs, ultimately contributing to safety assurances of HRSs in Republic of Korea.
Investigation of the Effects of Infrared and Hot Air Oven Drying Methods on Drying Behaviour and Colour Parameters of Red Delicious Apple Slices
Authors: Dajbych Oldřich , Kabutey Abraham , Mizera Čestmír , Herák David
Published: October 2023

This present study investigated thin-layer drying characteristics of dried apple slices for a range of temperatures from 40 °C to 80 °C at a constant drying time of 10 h under infrared (IR) and hot air oven (OV) drying methods. The fresh apples were cut into a cylindrical size of thickness of 8.07 ± 0.05 mm and a diameter of 66.27 ± 3.13 mm. Fourteen thin-layer mathematical models available in the literature were used to predict the drying process. The goodness of fit of the drying models was assessed by the root mean square error (RMSE), chi-square (χ2), coefficient of determination (R2) and modelling efficiency (EF). The results showed that the lightness and greenness/redness of the dried sample, total colour change, chroma change, colour index, whiteness index, bulk density, final surface area and final volume significantly (p-value < 0.05) correlated with the drying temperature under IR. Under OV, however, only the final surface area and bulk density of the dried samples showed significant (p-value < 0.05) with the drying temperature. Shrinkage values for OV and IR methods showed both increasing and decreasing trends along with the drying temperatures. The Weibull distribution model proved most suitable for describing the drying processes based on the statistical validation metrics of the goodness of fit. In future studies, the combined effect of the above-mentioned drying methods and other drying techniques on apple slices among other agricultural products should be examined to obtain a better insight into the drying operations and quality improvement of the final product for preservation and consumer acceptability.
“Faith-Sensitive” Mental Health and Psychosocial Support in Pluralistic Settings: A Spiritual Care Perspective
Authors: Winiger Fabian , Goodwin Ellen
Published: October 2023

Over the past two decades, in response to a growing awareness of the impacts of humanitarian crises on mental health and psychosocial well-being, leading UN agencies and international aid organisations have developed a comprehensive framework for Mental Health and Psychosocial Support (MHPSS). In more recent years, aid workers have further begun to consider religious life as a central factor in mental health and psychosocial well-being, viewing “faith” as an important, but often neglected, component of empowering and “locally appropriate” MHPSS. However, the attempt to deliver “faith-sensitive” MHPSS across the highly pluralistic settings of international humanitarian intervention has entailed protracted ethical and practical challenges. In this article, we argue that these challenges may be usefully understood in terms of three areas of concern: the lack of evidence on effective interventions; the risk of reproducing problematic power dynamics between MHPSS providers and receivers; and the challenge of articulating a cross-culturally relevant paradigm of “faith-sensitivity” comprehensible across a wide range of religiously diverse settings. This article contributes to these challenges by drawing on the field of professional spiritual care to suggest areas of potential contribution and interdisciplinary dialogue.
The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data
Authors: Mu Qinglu , Wang Changqing , Zhong Min , Yan Yihao , Liang Lei
Published: October 2023

The electrostatic gravity gradiometer carried by the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite is affected by accelerometer noise and other factors; hence, the observation data present complex error characteristics in the low-frequency domain. The accuracy of the recovered gravity field will be directly affected by the design of the filters based on the error characteristics of the gradient data. In this study, the applicability of various filters to different errors in observation is evaluated, such as the 1/f error and the orbital frequency errors. The experimental results show that the cascade filter (DARMA), which is formed of a differential filter and an autoregressive moving average filter (ARMA) filter, has the best accuracy for the characteristic of the 1/f low-frequency error. The strategy of introducing empirical parameters can reduce the orbital frequency errors, whereas the application of a notch filter will worsen the final solution. Frequent orbit changes and other changes in the observed environment have little impact on the new version gradient data (the data product is coded 0202), while the influence cannot be ignored on the results of the old version data (the data product is coded 0103). The influence can be effectively minimized by shortening the length of the arc. By analyzing the above experimental findings, it can be concluded that the inversion accuracy can be effectively improved by choosing the appropriate filter combination and filter estimation frequency when solving the gravity field model based on the gradient data of the GOCE satellite. This is of reference significance for the updating of the existing models.
Analysis of the Controlling Effect of Excess Topography on the Distribution of Coseismic Landslides during the Iburi Earthquake, Japan, on 6 September 2018
Authors: Zhang Pengfei , Qiu Hengzhi , Xu Chong , Chen Xiaoli , Zhou Qing
Published: October 2023

Coseismic landslides cause changes in the hillside material, and this erosion process plays an important role in the evolution of the topography. Previous studies seldom involved research on the influence of excess topography on the occurrences of coseismic landslides. The Iburi earthquake, which occurred in Japan on 6 September 2018 and triggered a large number of landslides, provided a research example to explore the relationship between coseismic landslides and excess topography. We used the average slope of the lithology as the threshold slope of the corresponding stratum to calculate the excess topography of the different lithological units. Based on the advanced spaceborne thermal emission and reflection radiometer (ASTER) digital elevation model (DEM) with a resolution of 30 m, a quantitative analysis was conducted on the excess topography in the study area. The results indicate that the excess topography in the study area was mainly distributed in the valleys on both sides of the river, and the thickness of the excess topography on the high and steep ridges was generally greater than that at the foot of the slope, which has a relatively flat topography or a low elevation. In the area affected by the earthquake, approximately 94.66% of the coseismic landslides (with an area of approximately 28.23 m2) developed in the excess topography area, indicating that the distribution of the excess topography had a strong controlling influence on the spatial distribution of the coseismic landslides. The Iburi earthquake mainly induced shallow landslides, but the thickness of the landslide body was much smaller than the excess topography height in the landslides-affected area. This may imply that the excess topography was not completely removed by the coseismic landslides, and the areas where the earthquake landslides occurred still have the possibility of producing landslides in the future.
A Multi-Scenario Prediction and Spatiotemporal Analysis of the Land Use and Carbon Storage Response in Shaanxi
Authors: Wei Xindong , Zhang Shuyuan , Luo Pingping , Zhang Shuomeng , Wang Huanyuan , Kong Dehao , Zhang Yuanyuan , Tang Yang , Sun Shuo
Published: October 2023

The role of carbon sequestration in terrestrial ecosystems is crucial for achieving carbon neutrality. This study primarily focuses on examining the carbon storage in Shaanxi Province under different land-use scenarios. This study employed the LP-PLUS-InVEST model to explore the characteristics and spatial and temporal changes in carbon storage across four scenarios (business-as-usual (BUS), ecological protection (EPS), water–energy–food (WEF), and rural revitalization (RRS)) in Shaanxi Province. The results show that from 2000 to 2020, the carbon storage in Shaanxi Province is on a decreasing trend mainly due to the large occupation of ecological land by economic development. EPS has the largest increase in carbon storage under the four scenarios in 2030 and 2060. On the contrary, BUS has a rapid expansion of construction land, which leads to a gradual decreasing trend in carbon storage. WEF has a gradual increasing trend in carbon storage, while RRS has a trend of increasing and then slowly decreasing carbon storage. The spatial distribution trends of carbon storage in all scenarios were similar; high-carbon-reserve areas were mainly distributed in southern and central Shaanxi, which has a better ecological environment and less construction land, while low-value areas were distributed in the Central Shaanxi Plain, which has high land-use intensity. In terms of the stability of carbon reserves, the stable areas are predominantly concentrated in the Qinling Mountains, while the unstable areas are concentrated in the plain urban areas. Specifically, returning cultivated land to forest and grassland is an important initiative to promote the increase in carbon storage in Shaanxi Province. The decrease in carbon storage is mainly affected by strong urban expansion. Our study optimizes the land-use pattern according to the development needs of Shaanxi Province, and promotes the integrated development of ecological protection, food security, and economic development. Guidance is provided to promote regional carbon neutrality.
Resistance of Grassland under Different Drought Types in the Inner Mongolia Autonomous Region of China
Authors: Guo Jian , Yang Xiuchun , Jiang Weiguo , Xing Xiaoyu , Zhang Min , Chen Ang , Yang Dong , Yang Mingxin , Wei Lunda , Xu Bin
Published: October 2023

The increasing frequency of global drought events poses a significant threat to the stability of grassland ecosystems’ functionality. The Inner Mongolian grasslands stand out as one of the world’s most drought-prone regions, facing elevated drought risks compared to other biomes. An in-depth comprehension of the impact of drought on grassland ecosystems is paramount for their long-term sustainability. Using the Standardized Precipitation Evapotranspiration Index (SPEI) from 1982 to 2018, this study identified various drought events within the Inner Mongolian grasslands, encompassing moderate drought, severe drought, and extreme drought. The resistance of the vegetation to the different drought conditions, assessed through net primary productivity (NPP) as a metric (reflecting its capacity to maintain its original level during drought periods), was examined. The research findings indicated that the period from 2001 to 2018 witnessed a substantial increase in both the frequency and the extent of drought events compared to the period from 1982 to 2000, particularly concerning severe and extreme droughts. The areas most severely impacted by extreme drought were the Xilingol League and the Alxa League. From 1982–2000 to 2001–2018, under moderate drought conditions, vegetation resistance exhibited a minor decrease in the central and eastern regions but experienced a slight increase in the western region. In contrast, under severe drought conditions, the western region saw a significant decrease in vegetation resistance. Remarkably, under extreme drought conditions, the western region showed a substantial increase in vegetation resistance, while the central and eastern regions experienced a slight decrease. Across all three drought conditions, as precipitation levels declined, the resistance of the meadow–steppe–desert ecosystems demonstrated a high–low–high distribution pattern. The temperate desert steppe exhibited a minimal vulnerability to drought, boasting resistance levels exceeding 0.9. Notably, extreme drought had the most pronounced impact on the temperate meadow steppe, temperate steppe, and temperate desert steppe, particularly within the temperate meadow steppe category. Given these findings, the authorities responsible for grassland management should prioritize regions characterized by frequent drought occurrences and low drought resistance, such as Ulanqab City, the Xilingol League, and the western part of Hulun Buir City. Safeguarding steppe ecosystems is of paramount importance for stabilizing vegetation productivity and land carbon sinks, especially under the anticipated exacerbation of climate conditions in the future.
Two-Step Correction Based on In-Situ Sound Speed Measurements for USBL Precise Real-Time Positioning
Authors: Zhao Shuang , Liu Huimin , Xue Shuqiang , Wang Zhenjie , Xiao Zhen
Published: October 2023

The ultra-short baseline (USBL) positioning system has been widely used for autonomous and remotely operated vehicle (ARV) positioning in marine resource surveying and ocean engineering fields due to its flexible installation and portable operation. Errors related to the sound speed are a critical factor limiting the positioning performance. The conventional strategy adopts a fixed sound velocity profile (SVP) to correct the spatial variation, especially in the vertical direction. However, SVP is actually time-varying, and ignoring this kind of variation will lead to a worse estimation of ARVs’coordinates. In this contribution, we propose a two-step sound speed correction method, where, firstly, the deviation due to the acoustic ray bending effect is corrected by the depth-based ray-tracing policy with the fixed SVP. Then, the temporal variation of SVP is considered, and the fixed SVP is adaptively adjusted according to the in situ sound velocity (SV) measurements provided by the conductivity–temperature–depth (CTD) sensor equipped at the ARV. The proposed method is verified by semi-physical simulation and sea-trail dataset in the South China Sea. When compared to the fixed-SVP method, average positioning accuracy with the resilient SVP be improved by 8%, 21%, and 26% in the east, north, and up directions, respectively. The results demonstrate that the proposed method can efficiently improve the adaptability of sound speed observations and deliver better performance in USBL real-time positioning.
Improved UNet with Attention for Medical Image Segmentation
Authors: AL Qurri Ahmed , Almekkawy Mohamed
Published: October 2023

Medical image segmentation is crucial for medical image processing and the development of computer-aided diagnostics. In recent years, deep Convolutional Neural Networks (CNNs) have been widely adopted for medical image segmentation and have achieved significant success. UNet, which is based on CNNs, is the mainstream method used for medical image segmentation. However, its performance suffers owing to its inability to capture long-range dependencies. Transformers were initially designed for Natural Language Processing (NLP), and sequence-to-sequence applications have demonstrated the ability to capture long-range dependencies. However, their abilities to acquire local information are limited. Hybrid architectures of CNNs and Transformer, such as TransUNet, have been proposed to benefit from Transformer’s long-range dependencies and CNNs’ low-level details. Nevertheless, automatic medical image segmentation remains a challenging task due to factors such as blurred boundaries, the low-contrast tissue environment, and in the context of ultrasound, issues like speckle noise and attenuation. In this paper, we propose a new model that combines the strengths of both CNNs and Transformer, with network architectural improvements designed to enrich the feature representation captured by the skip connections and the decoder. To this end, we devised a new attention module called Three-Level Attention (TLA). This module is composed of an Attention Gate (AG), channel attention, and spatial normalization mechanism. The AG preserves structural information, whereas channel attention helps to model the interdependencies between channels. Spatial normalization employs the spatial coefficient of the Transformer to improve spatial attention akin to TransNorm. To further improve the skip connection and reduce the semantic gap, skip connections between the encoder and decoder were redesigned in a manner similar to that of the UNet++ dense connection. Moreover, deep supervision using a side-output channel was introduced, analogous to BASNet, which was originally used for saliency predictions. Two datasets from different modalities, a CT scan dataset and an ultrasound dataset, were used to evaluate the proposed UNet architecture. The experimental results showed that our model consistently improved the prediction performance of the UNet across different datasets.
Analysis of Connectome Graphs Based on Boundary Scale
Authors: Moron-Fernández María José , Amedeo Ludovica Maria , Monterroso Muñoz Alberto , Molina-Abril Helena , Díaz-del-Río Fernando , Bini Fabiano , Marinozzi Franco , Real Pedro
Published: October 2023

The purpose of this work is to advance in the computational study of connectome graphs from a topological point of view. Specifically, starting from a sequence of hypergraphs associated to a brain graph (obtained using the Boundary Scale model, BS2), we analyze the resulting scale-space representation using classical topological features, such as Betti numbers and average node and edge degrees. In this way, the topological information that can be extracted from the original graph is substantially enriched, thus providing an insightful description of the graph from a clinical perspective. To assess the qualitative and quantitative topological information gain of the BS2 model, we carried out an empirical analysis of neuroimaging data using a dataset that contains the connectomes of 96 healthy subjects, 52 women and 44 men, generated from MRI scans in the Human Connectome Project. The results obtained shed light on the differences between these two classes of subjects in terms of neural connectivity.
An Infrared Small Target Detection Method Based on Attention Mechanism
Authors: Wang Xiaotian , Lu Ruitao , Bi Haixia , Li Yuhai
Published: October 2023

The human visual attention system plays an important role in infrared target recognition because it can quickly and accurately recognize infrared small targets and has good scene adaptability. This paper proposes an infrared small target detection method based on an attention mechanism, which consists of three modules: a bottom-up passive attention module, a top-down active attention module, and decision feedback equalization. In the top-down active attention module, given the Gaussian characteristics of infrared small targets, the idea of combining knowledge-experience Gaussian shape features is applied to implement feature extraction, and quaternion cosine transform is performed to achieve multi-dimensional fusion of Gaussian shape features, thereby achieving complementary fusion of multi-dimensional feature information. In the bottom-up passive attention module, considering that the difference in contrast and motion between the target and the background can attract attention easily, an optimal fast local contrast algorithm and improved circular pipeline filtering are adopted to find candidate target regions. Meanwhile, the multi-scale Laplacian of the Gaussian filter is adopted to estimate the optimal size of the infrared small target. The fast local contrast algorithm based on box filter acceleration and structure optimization is employed to extract local contrast features, and candidate target regions can be obtained by using an adaptive threshold. Besides, the mean gray, target size, Gaussian consistency, and circular region constraint are used in pipeline filtering to extract motion regions, and the false-alarm rate is reduced effectively. Finally, decision feedback equalization is adopted to obtain real targets. Experiments are conducted on some real infrared images involving complex backgrounds with sea, sky, and ground clutters, and the experimental results indicate that the proposed method can achieve better detection performance than conventional baseline methods, such as RLCM, ILCM, PQFT, MPCM, and ADMD. Also, mathematical proofs are provided to validate the proposed method.
Application of the Lamb Wave Mode of Acoustic Emission for Monitoring Impact Damage in Plate Structures
Authors: Xu Baochun , Huang Jiacai , Jie Yachun
Published: October 2023

The impact acoustic emission (AE) of plate structures is a transient stress wave generated by local materials under impact force that contains the state information of the impacted area. If the impact causes damage, the AE from material damage will be superimposed on the impact AE. Therefore, this paper details the direct extraction of damage-induced AEs from impact AEs for the health monitoring of plate structures. The damage-induced AE was analysed based on various aspects, including the cut-off range and propagation speed characteristics of the Lamb wave mode, the correlation between the force direction and the Lamb wave mode, and the impact damage process. According to these features, the damage-induced AE wave packets were extracted and verified via impact tests on epoxy glass fibreboards. The results demonstrated the feasibility of the proposed method for determining whether an impact causes damage via the direct extraction of the damage-induced AE from the impact AE.
Real-Time Anomaly Detection for Water Quality Sensor Monitoring Based on Multivariate Deep Learning Technique
Authors: El-Shafeiy Engy , Alsabaan Maazen , Ibrahem Mohamed I. , Elwahsh Haitham
Published: October 2023

With the increased use of automated systems, the Internet of Things (IoT), and sensors for real-time water quality monitoring, there is a greater requirement for the timely detection of unexpected values. Technical faults can introduce anomalies, and a large incoming data rate might make the manual detection of erroneous data difficult. This research introduces and applies a pioneering technology, Multivariate Multiple Convolutional Networks with Long Short-Term Memory (MCN-LSTM), to real-time water quality monitoring. MCN-LSTM is a cutting-edge deep learning technology designed to address the difficulty of detecting anomalies in complicated time series data, particularly in monitoring water quality in a real-world setting. The growing reliance on automated systems, the Internet of Things (IoT), and sensor networks for continuous water quality monitoring is driving the development and deployment of the MCN-LSTM approach. As these technologies become more widely used, the rapid and precise identification of unexpected or aberrant data points becomes critical. Technical difficulties, inherent noise, and a high data influx pose significant hurdles to manual anomaly detection processes. The MCN-LSTM technique takes advantage of deep learning by integrating Multiple Convolutional Networks and Long Short-Term Memory networks. This combination of approaches offers efficient and effective anomaly detection in multivariate time series data, allowing for identifying and flagging unexpected patterns or values that may signal water quality issues. Water quality data anomalies can have far-reaching repercussions, influencing future analyses and leading to incorrect judgments. Anomaly identification must be precise to avoid inaccurate findings and ensure the integrity of water quality tests. Extensive tests were carried out to validate the MCN-LSTM technique utilizing real-world information obtained from sensors installed in water quality monitoring scenarios. The results of these studies proved MCN-LSTM’s outstanding efficacy, with an impressive accuracy rate of 92.3%. This high level of precision demonstrates the technique’s capacity to discriminate between normal and abnormal data instances in real time. The MCN-LSTM technique is a big step forward in water quality monitoring. It can improve decision-making processes and reduce adverse outcomes caused by undetected abnormalities. This unique technique has significant promise for defending human health and maintaining the environment in an era of increased reliance on automated monitoring systems and IoT technology by contributing to the safety and sustainability of water supplies.
Study of Settlement Patterns in Farming–Pastoral Zones in Eastern Inner Mongolia Using Planar Quantization and Cluster Analysis
Authors: Xu Hui , Guo Qin , Siqin Chaoketu , Li Yingjie , Gao Fei
Published: October 2023

Settlements are comprehensive carriers of the material form expression and social appearance of human activities under specific geographical environmental choices. The analysis and preservation of their forms are important principles and strategies for rural settlement planning and construction. In this study, 28 settlements in the farming–pastoral zones in eastern Inner Mongolia were selected as the research objects. By combining fractal geometry and computer programming, the relationship between the boundary form, spatial structure, and architectural order of the settlements was quantitatively expressed, and quantitative indicators that better summarize the form of the settlements in the farming–pastoral zones in eastern Inner Mongolia were extracted. Then, factor analysis and cluster analysis were conducted using the Statistical Package for the Social Sciences software (SPSS26.0) to obtain the characteristic types of settlement forms. Finally, the classification results were combined with social and humanistic factors and the geographical environment to test the rationality of the results. The results show that (1) five form indicators effectively describe the settlement forms in the research area, among which the shape index, dimension of the public space, and architectural density play a crucial role in the spatial structure factors. (2) In this study, we mainly used a data collection and processing–principal component extraction and systematic clustering-type division method to complete scientific research on settlement form classification. (3) By combining the clustering results with the spatial form features and analysis mainly based on spatial structure factors, the settlement forms in the farming–pastoral zones in eastern Inner Mongolia are described as three typical types: multidirectional expanding settlement, settlement patterns extending at both ends, and centripetal development settlement. Furthermore, the characteristics of the human–land relationship implicit in each type of settlement form are explained, achieving a scientific representation and classification of the settlement forms. The research results provide useful quantitative guidance for rural revitalization, settlement form optimization, and preservation in the farming–pastoral zones in eastern Inner Mongolia
Valorization of Grape Pomace for Trametes versicolor Mycelial Mass and Polysaccharides Production
Authors: Kachrimanidou Vasiliki , Alexandri Maria , Papapostolou Harris , Papadaki Aikaterini , Kopsahelis Nikolaos
Published: October 2023

Polysaccharides and protein–polysaccharide complexes produced from the fungal strain Trametes versicolor have demonstrated bioactive properties that depend on the substrate, the fermentation conditions and also the fungal strain. Likewise, the submerged and controlled fermentation of medicinal mushrooms elicits numerous advantages over traditional processes to produce mycelia and added-value products, along with the exploitation of biodiversity. This study evaluated the growth profile of an indigenous T. versicolor isolate using commercial nutrients that were subsequently replaced with renewable resources, specifically, grape pomace extract (GPE), under static and shaking conditions. The effect of elicitor addition was also assessed using GPE. The process productivity was significantly improved, yielding 21 g/L of biomass. Agitation proved beneficial for all examined cases regarding biomass productivity and substrate consumption rates. The chemical and antioxidant profile of crude intracellular and extracellular polysaccharides was determined, whereby intracellular extracts indicated >50% antioxidant activity. FTIR analysis validated the preliminary chemical characterization of the extracts, whereas the amino acid profile of IPS extracts was also included. Evidently, our study elaborates on the development of a bioconversion concept to valorize wine-making side-streams to formulate added-value products with potential bioactive attributes.
The Impact of Agricultural Employment and Technological Innovation on the Environment: Evidence from BRICS Nations Considering a Novel Environmental Sustainability Indicator
Authors: Jiaduo Erti , Kibria Md. Golam , Aspy Nazhat Nury , Ullah Ehsan , Hossain Md. Emran
Published: October 2023

This study fills a gap created by previous environmental investigations by including the impact of agricultural employment and technology on the load capacity factor (LCF) rather than solely focusing on CO2 or greenhouse gas (GHG) emissions, which only measure from the demand side; LCF provides a complete picture of environmental degradation by evaluating both the demand side and supply side. This connection is moderated further by considering the renewable energy and natural resource rent impacts. In this analysis, panel econometric methods are incorporated, including the cross-sectional dependence test. This study uses the Pooled Mean Group–Autoregressive Distributed Lag (PMG-ARDL) model to evaluate the level of effect independent factors had on the LCF of the BRICS (Brazil, Russia, India, China, and South Africa) nations from 1992 to 2020 in the presence of a heterogeneous integration order. The estimations recognize heterogeneity in the effects of agricultural employment, renewable energy, natural resource rent, and technology on LCF, in the short run and long run. According to the empirical results, agricultural employment significantly enhances the LCF both in the short run and long run, implying that employment in agriculture improves environmental sustainability. However, increasing the use of renewable energy protects the environment from degradation only in the long run; it has no significant impact in the short run. On the contrary, natural resource rent and technology lead to a decline in environmental sustainability in the long run. Hence, this study recommends prioritizing renewable energy intake over other energies, providing proper incentives to motivate agricultural entrepreneurship to ensure a sustainable environment.
The Design and Experimental Study of a Double-Column Scrambler Wind–Sand Separator for Sustainable Soil Wind Erosion Monitoring
Authors: Cai Xuyang , Hao Baoer , Liu Haiyang , Tong Xin , Guo Mengjun , Hou Zhanfeng
Published: October 2023

Sand collectors play an indispensable role in the study of land desertification, with the wind–sand separator serving as a vital core component. It plays a pivotal role in researching soil wind erosion. In response to the challenge of wind–sand separation in high-wind conditions, we introduce a novel approach. We designed, optimized, and validated a double-column scrambler wind–sand separator through computational fluid dynamics (CFD) simulations and wind tunnel experiments. Our test results showcased the impressive performance of this double-column scrambler wind–sand separator. It achieved substantial reductions in wind velocities at both the exhaust and sandfall ports, with reductions of 89.56% and 89.85%, respectively. Furthermore, the wind–sand separation efficiency consistently exceeded 98% across wind speeds ranging from 6 to 15 m/s. This study establishes a robust scientific foundation for further enhancements in the performance of the double-column scrambler wind–sand separator, holding promise for advancements in the field of desertification monitoring and control.
Developing a Tool for Landscape Sustainability Assessment—Using a New Conceptual Approach in Lebanon
Authors: Aad Roula , Nemer Nabil
Published: October 2023

In the absence of a holistic view of landscape sustainability, credible data and consistent information are needed to help decision-making and support adaptive landscape management. This course of events highlights a strong need for a tool (system of standards and controls) that can be used by multiple stakeholders (such as NGOs, public authorities, cooperatives, associations, higher education institutes, etc.) to analyze the state and sustainability of landscapes, predict any impact of new projects on the landscape, and develop urban and peri-urban planning policies. However, while consolidated tools of assessment exist, they exhibit complexity in their references. Existing assessment tools also lack specificity and are primarily limited to qualitative approaches. Although large sets of indicators are available and can be adopted, it is crucial to select a new set of non-conventional indicators that provide a holistic view of the various dimensions of the landscape. This review article aims primarily to discuss relevant models and prerequisites in order to later develop landscape indicators to complement—and in many cases—replace existing agro-ecological indicators. Landscape indicators will serve as a baseline for the proposed tool, which will employ a mixed methodology based on both qualitative and quantitative indicators. Additionally, various environmental and landscape indicators are presented and compared to identify the best reference to landscape sustainability. Various fields of application for indicators-based tools and the scales on which they can be applied are also considered. In particular, Lebanese landscapes exhibit variability in characteristics and possess a unique identity with genuine natural and built landscapes. Only recently has there been an increasing interest in sustainability assessment, particularly in relation to Lebanese Landscapes. Unfortunately, there is a likely gap in the studies, planning, and policies related to these landscapes. A tool that can evaluate, protect, conserve, and propose concrete solutions for these landscapes are needed more than ever.
Optimal Dispatch and Control Strategy of Park Micro-Energy Grid in Electricity Market
Authors: Zheng Qunru , Yang Ping , Wu Yuhang , Xu Zhen , Zhang Peng
Published: October 2023

In the existing research on the dispatch and control strategies of park micro-energy grids, the dispatch and control characteristics of controllable energy units, such as response delay, startup and shutdown characteristics, response speed, and sustainable response time, have not been taken into account. Without considering the dispatch and control characteristics of the controllable energy units, substantial deviation will occur in the execution of optimized dispatch and control strategies, resulting in economic losses in the electricity market and adverse effects on the safe operation of power systems. This paper proposes a unified model to describe the dispatch and control characteristics of various types of controlled energy units, based on which we develop a three-tier optimization dispatch and control strategy for the micro-energy grid, involving day-ahead, intra-day, and real-time stages. The day-ahead and intra-day optimization dispatch strategy is implemented to obtain the optimal reference values in the real-time stage for each controllable energy unit. In the real-time stage, a minimum variance control strategy based on d-step prediction is proposed. By considering the multi-dimensional control characteristics of controllable energy units, the real-time predictive control strategy aims to ensure that the controllable energy units can precisely follow the optimized dispatch plan. The simulation results show that when compared with the dispatching method optimized by the improved quantum particle swarm algorithm, the adoption of the optimal dispatch and control strategy proposed in this paper resulted in a 45.79% improvement in execution accuracy and a 2.38% reduction in the energy cost.