bluuebunny/crossref_metadata_2025 huggingface dataset:
NOX Concentration Prediction in Cement Denitrification Process Based on EEMD-MImRMR-BASBP
Authors: Liu Xuanzhi , Chen Yanxin , He Ning , Yao Yanfei
Published: January 2023

NOx concentration is an important indicator of the response to ammonia dosage and nitrogen emissions, and its accurate prediction allows for efficient and rational optimal control of ammonia dosage. Due to the large external noise, time lag and non-linearity of the cement denitrification process, it is difficult to derive accurate mathematical prediction models. Therefore, a new machine learning model, namely EEMD-MImRMR-BASBP, is developed. Firstly, Ensemble Empirical Mode Decomposition (EEMD) and median-averaged filtering is used to process the data and remove the noise. In order to handle the large time lags, non-linearity and non-smoothness among the variables, mutual information (MI) based on the entropy principle is proposed to calculate the lag time of the non-linear system; furthermore, according to the feature variable selection method of Max-Relevance and Min-Redundancy (mRMR), the factors with strong influence are selected as the input variables of the prediction model in combination with the results of the mechanism analysis. Then, the EEMD-MImRMR-BASBP model to predict NOX concentration is constructed, in which the initialization parameters of the Back Propagation Neural Network (BP) are searched by Beetle Antennae Search (BAS) to effectively overcome the parameter selection problem of traditional BP prediction models. Finally, the model was applied for the NOX concentration prediction of a real cement plant in Jiang xi and Fu ping and compared with the classical BP-based prediction model, BASBP model, the root means square error (RMSE) and mean absolute error (MAE) of the EEMD-MImRMR-BASBP model for the two production lines are only 0.2927, 0.3513 and 0.1795, and 0.2383, which have better prediction performance compared with the current model.
Acknowledgment to the Reviewers of Processes in 2022
Authors:   Processes Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Microwave-Assisted Freeze-Drying with Frequency-Based Control Concepts via Solid-State Generators: A Simulative and Experimental Study
Authors: Sickert Till , Kalinke Isabel , Christoph Jana , Gaukel Volker
Published: January 2023

Freeze-drying is a common process to extend the shelf life of food and bioactive substances. Its main drawback is the long drying time and associated high production costs. Microwaves can be applied to significantly shorten the process. This study investigates the effects of modulating the electromagnetic field in microwave-assisted freeze-drying (MFD). Control concepts based on microwave frequency are evaluated using electromagnetic simulations. The concepts are then applied to the first part of primary drying in a laboratory-scale system with solid-state generators. Targeted frequency modulation in the electromagnetic simulations enabled an increase in energy efficiency or heating homogeneity throughout MFD while having negligible effects on the power dissipation ratio between frozen and dried product areas. The simulations predicted the qualitative effects observed in the experimental proof of concept regarding energy efficiency and drying homogeneity. Additionally, shortened drying times were observed in the experiments with a targeted application of energy-efficient frequencies. However, differences occurred in the quantitative validation of the electromagnetic models for energy efficiency in dependence on frequency. Nevertheless, the models can be used for a time-efficient investigation of the qualitative effects of the control concepts. In summary, frequency-based control of MFD represents a promising approach for process control and intensification.
Micro-Stepping Motor for Instrument Panel Using PWM Drive Method
Authors: Tsai Pu-Sheng , Wu Ter-Feng , Chen Jen-Yang , Teng Ping-Tse
Published: January 2023

This study presents a pointer-driven controller for an instrument panel. The proposed pointer utilizes the permanent magnet (PM) stepping motor produced by the Japanese company NMB. This stepping motor is vibration-proof and tolerates noise jamming as well as wind and rain exposure. Moreover, it has no mechanical structures and is low cost. Most importantly, it features accurate positioning; therefore, it can be used to measure vehicle speed, engine speed, fuel capacity, and temperature. However, the PM stepping motor of the NMB pointer requires 10 degrees for each step, and this low resolution results in roll hesitation as its steps. The aim of the current paper was to solve the problems of the large angle size and low resolution associated with this stepping motor. Based on two-phase excitation, we propose driving the motor using pulse width modulation (PWM). Specifically, we divided each 10-degree step into 100 equal parts. In other words, every step is 0.1 degrees. The resolution of pointer rotation can be increased by 100-fold by using the approach proposed in this paper. When applied to vehicle (or locomotive) instruments, the pointer can move very smoothly on the tachometer or oil gauge.
Molecular and Cellular Responses to Ionization Radiation in Untransformed Fibroblasts from the Rothmund–Thomson Syndrome: Influence of the Nucleo-Shuttling of the ATM Protein Kinase
Authors: Al-Choboq Joëlle , Nehal Myriam , Sonzogni Laurène , Granzotto Adeline , El Nachef Laura , Restier-Verlet Juliette , Maalouf Mira , Berthel Elise , Aral Bernard , Corradini Nadège , Bourguignon Michel , Foray Nicolas
Published: January 2023

The Rothmund–Thomson syndrome (RTS) is a rare autosomal recessive disease associated with poikiloderma, telangiectasias, sun-sensitive rash, hair growth problems, juvenile cataracts and, for a subset of some RTS patients, a high risk of cancer, especially osteosarcoma. Most of the RTS cases are caused by biallelic mutations of the RECQL4 gene, coding for the RECQL4 DNA helicase that belongs to the RecQ family. Cellular and post-radiotherapy radiosensitivity was reported in RTS cells and patients since the 1980s. However, the molecular basis of this particular phenotype has not been documented to reliably link the biological and clinical responses to the ionizing radiation (IR) of cells from RTS patients. The aim of this study was therefore to document the specificities of the radiosensitivity associated with RTS by examining the radiation-induced nucleo-shuttling of ATM (RIANS) and the recognition and repair of the DNA double-strand breaks (DSB) in three skin fibroblasts cell lines derived from RTS patients and two derived from RTS patients’ parents. The results showed that the RTS fibroblasts tested were associated with moderate but significant radiosensitivity, a high yield of micronuclei, and impaired DSB recognition but normal DSB repair at 24 h likely caused by a delayed RIANS, supported by the sequestration of ATM by some RTS proteins overexpressed in the cytoplasm. To our knowledge, this report is the first radiobiological characterization of cells from RTS patients at both molecular and cellular scales.
The Janus-Faced Clergy Crimes in the Judge Dee Mysteries: A Pentadic Criticism
Authors: Xie Pan , Li Zhou
Published: January 2023

Robert Van Gulik, one of the twentieth century’s most prominent sinologists and detective writers, has made significant contributions to the study of Chinese cultures but received inadequate scholarly appraisal until the twenty-first century. Although Van Gulik’s Judge Dee mysteries have been well received informally among ordinary readers and scholars, little academic attention has been devoted to Judge Dee’s trials of evil clergy due to their covert representation in Van Gulik’s narration. This paper pays attention to crimes committed by religious leaders and members of orders to reveal an implicit religion-crime relationship in Van Gulik’s works on Judge Dee with the help of Kenneth Burke’s pentadic criticism. In our analysis, we find that Van Gulik differentiates between good and evil disciples, the acts of the disciples and the beliefs of religions, and non-mainstream and orthodox religion, presenting a heterogeneous religious crime landscape. As a result, in the misdeeds of clergy and offenses against the sacred religion, a Janus-faced (two-faced) clergy crime is identified in the mysteries.
Evaluation of Ocular Biometric Parameters Following Cataract Surgery
Authors: Teodoru Cosmin Adrian , Cerghedean-Florea Maria-Emilia , Tănăsescu Ciprian , Dura Horațiu , Fleacă Radu , Munteanu Mihnea , Stanca Horia , Popescu Florina Georgeta , Roman Mihai Dan , Nicula Gheorghe Zsolt , Matei Horea Vladi , Vică Mihaela Laura
Published: January 2023

Background: The aim of this study was to highlight the structural changes in patients with cataract following surgery and the repercussions on the anterior pole. Methods: A total of 83 patients diagnosed with cataract who underwent uneventful phacoemulsification was included. Every patient was examined one week prior to and two weeks after the surgery. Pre- and postoperative assessment included examination of the anterior and posterior segment, keratometry, and optical biometry. Results: The pre- vs. postoperative axial length (AL) mean difference was 0.07 ± 0.18 mm (p < 0.001).The mean difference of the postoperative anterior chamber depth (ACD) vs. preoperative ACD values (1.11 ± 0.50 mm) was also statistically significant (p < 0.001). The linear regression function postoperative central corneal thickness (CCT) = 0.9004 × (preoperative CCT) + 0.0668, where it characterized a reduced positive correlation (R2) of 68.89% between the postoperative CCT and preoperative CCT. The mean pre-/post-operative differences in the K1 values were 0.08 ± 0.38 D, with a statistically significant difference between the two datasets (p = 0.0152). The mean pre/postoperative difference in the K2 values was 0.002 ± 0.58 D (p = 0.4854). Conclusions: ACD deepened significantly postoperatively. Regarding AL, there was a decrease after surgery, and a very good positive correlation between the post and preoperative values. The CCT values decreased with age. The 2.2-mm corneal incision during cataract surgery resulted in a relatively small postoperative residual astigmatism.
Transformable Wheelchair–Exoskeleton Hybrid Robot for Assisting Human Locomotion
Authors: Chaichaowarat Ronnapee , Prakthong Sarunpat , Thitipankul Siri
Published: January 2023

This paper presents a novel wheelchair–exoskeleton hybrid robot that can transform between sitting and walking modes. The lower-limb exoskeleton uses planetary-geared motors to support the hip and knee joints. Meanwhile, the ankle joints are passive. The left and right wheel modules can be retracted to the lower legs of the exoskeleton to prepare for walking or stepping over obstacles. The chair legs are designed to form a stable sitting posture to avoid falling while traveling on smooth surfaces with low energy consumption. Skateboard hub motors are used as the front driving wheels along with the rear caster wheels. The turning radius trajectory as the result of differential driving was observed in several scenarios. For assisting sit-to-stand motion, the desired joint velocities are commanded by the user while the damping of the motors is set. For stand-to-sit motion, the equilibrium of each joint is set to correspond to the standing posture, while stiffness is adjusted on the basis of assistive levels. The joint torques supported by the exoskeleton were recorded during motion, and leg muscle activities were studied via surface electromyography for further improvement.
Airborne Millimeter-Wave InSAR Terrain Mapping Experiments Based on Automatic Extraction and Interferometric Calibration of Tie-Points
Authors: Zhang Bin , Xie Futai , Wang Liuliu , Li Shuang , Wei Lideng , Feng Liang
Published: January 2023

Limited by meteorological conditions, airspace, complex terrain and other factors, airborne millimeter-wave InSAR will inevitably face the situation of no control point layout when acquiring terrain data in the difficult mapping areas in Southwest China, which increases the difficulty of subsequent data processing. Moreover, the layout of control points in difficult mapping areas consumes a lot of manpower and time, which is not suitable for large-scale high-precision topographic mapping. To solve these problems, this paper proposes an automatic extraction of tie-points and interferometric calibration technology based on tie-points. This technology develops the automatic extraction algorithm of tie-points based on SAR + SIFT + RANSAC to obtain evenly distributed tie-points of adjacent images, and uses the evenly distributed tie-points as real known points to recalibrate the interference parameters, then carries out elevation transfer and elevation inversion through the tie-points of overlapping areas, thus realizing high-precision mapping without control points for airborne millimeter-wave InSAR. This paper uses measured data to verify the technology, and compares it with the areas with control points and marking points. The comparison results of elevation accuracy prove the feasibility and effectiveness of this method. This paper also discusses the difficulties in the treatment of typical areas, such as water areas, urban areas and mountain areas, and gives reasonable solutions that have good engineering application value.
Assessment of the IMERG Early-Run Precipitation Estimates over South American Country of Chile
Authors: da Silva Luciana , Mahmoud Mohammed , González-Rodríguez Lisdelys , Mohammed Safa , Rodríguez-López Lien , Arias Mauricio
Published: January 2023

Accurate rainfall measurement is a challenge, especially in regions with diverse climates and complex topography. Thus, knowledge of precipitation patterns requires observational networks with a very high spatial and temporal resolution, which is very difficult to construct in remote areas with complex geological features such as desert areas and mountains, particularly in countries with high topographical variability such as Chile. This study evaluated the performance of the near-real-time Integrated Multi-satellite Retrievals for GPM (IMERG) Early product throughout Chile, a country located in South America between 16°S–66°S latitude. The accuracy of the IMERG Early was assessed at different special and temporal scales from 2015 to 2020. Relative Bias (PBIAS), Mean Absolute Error (MAE), and Root-Mean-Squared Error (RMSE) were used to quantify the errors in the satellite estimates, while the Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) were used to evaluate product detection accuracy. In addition, the consistency between the satellite estimates and the ground observations was assessed using the Correlation Coefficient (CC). The spatial results show that the IMERG Early had the best performance over the central zone, while the best temporal performance was detected for the yearly precipitation dataset. In addition, as latitude increases, so do errors. Also, the satellite product tends to slightly overestimate the precipitation throughout the country. The results of this study could contribute towards the improvement of the IMERG algorithms and open research opportunities in areas with high latitudes, such as Chile.
Analysis of Wave Breaking on Gaofen-3 and TerraSAR-X SAR Image and Its Effect on Wave Retrieval
Authors: Zhong Ruozhu , Shao Weizeng , Zhao Chi , Jiang Xingwei , Zuo Juncheng
Published: January 2023

The main purpose of our work is to investigate the performance of wave breaking and its effect on wave retrieval in data acquired from the Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) at C-band and the German TerraSAR-X (TS-X) at X-band. The SAR images available for this study included 140 GF-3 images acquired in quad-polarization strip (QPS) mode and 50 dual-polarized (vertical-vertical (VV) and horizontal-horizontal (HH)) TS-X images acquired in stripmap (SM) mode. Moreover, these images were collocated with the waves simulated by the numeric WAVEWATCH-III (WW3) (version 5.16) model and HYbrid Coordinate Ocean Model (HYCOM) current. In particular, a few images covered the moored buoys monitored by the National Data Buoy Center (NDBC) of the National Oceanic and Atmospheric Administration (NOAA). The comparison between the WW3-simulated results and the significant wave heights (SWHs) from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA-5) showed that the correlation coefficient (COR) was 0.4–0.6 with a root mean squared error (RMSE) of about 0.2 m at SWHs of 0–4 m. The winds were inverted using VV-polarized geophysical model functions (GMFs), e.g., CSARMOD-GF for the GF-3 images and XMOD2 for the TS-X images. The Bragg resonant roughness in the normalized radar cross section (NRCS) was simulated using a radar backscattering model and the SAR-derived wind, WW3-simulated wave parameters, and HYCOM current. Then, the contribution of the non-polarized (NP) wave breaking to the SAR data was estimated by the VV-polarized NRCS, the HH-polarized NRCS, and the polarization ratio (PR) of the co-polarized Bragg resonant components in the NRCS. Because co-polarized Bragg resonant components in the NRCSs have poor results, due to the saturation for wind speeds greater than 20 m/s, the analysis of wave breaking is excluded at such conditions. The results revealed that the backscattering signal in the C-band was more sensitive to wave breaking than the backscattering signal in the X-band. Interestingly, the ratio had a linear correlation with wind speed. Moreover, the variation in the bias (inverted SWH minus WW3 simulation) showed that the bias increased as the wind speed (>8 m/s) and whitecap coverage (>0.005) increased. Following this rationale, wave retrieval during tropical cyclones should consider the influence of wave breaking.
Multi-Source Interactive Stair Attention for Remote Sensing Image Captioning
Authors: Zhang Xiangrong , Li Yunpeng , Wang Xin , Liu Feixiang , Wu Zhaoji , Cheng Xina , Jiao Licheng
Published: January 2023

The aim of remote sensing image captioning (RSIC) is to describe a given remote sensing image (RSI) using coherent sentences. Most existing attention-based methods model the coherence through an LSTM-based decoder, which dynamically infers a word vector from preceding sentences. However, these methods are indirectly guided through the confusion of attentive regions, as (1) the weighted average in the attention mechanism distracts the word vector from capturing pertinent visual regions and (2) there are few constraints or rewards for learning long-range transitions. In this paper, we propose a multi-source interactive stair attention mechanism that separately models the semantics of preceding sentences and visual regions of interest. Specifically, the multi-source interaction takes previous semantic vectors as queries and applies an attention mechanism on regional features to acquire the next word vector, which reduces immediate hesitation by considering linguistics. The stair attention divides the attentive weights into three levels—that is, the core region, the surrounding region, and other regions—and all regions in the search scope are focused on differently. Then, a CIDEr-based reward reinforcement learning is devised, in order to enhance the quality of the generated sentences. Comprehensive experiments on widely used benchmarks (i.e., the Sydney-Captions, UCM-Captions, and RSICD data sets) demonstrate the superiority of the proposed model over state-of-the-art models, in terms of its coherence, while maintaining high accuracy.
Ensemble Machine Learning for Mapping Tree Species Alpha-Diversity Using Multi-Source Satellite Data in an Ecuadorian Seasonally Dry Forest
Authors: Sesnie Steven , Espinosa Carlos , Jara-Guerrero Andrea , Tapia-Armijos María
Published: January 2023

The increased variety of satellite remote sensing platforms creates opportunities for estimating tropical forest diversity needed for environmental decision-making. As little as 10% of the original seasonally dry tropical forest (SDTF) remains for Ecuador, Peru, and Colombia. Remnant forests show high rates of species endemism, but experience degradation from climate change, wood-cutting, and livestock-grazing. Forest census data provide a vital resource for examining remote sensing methods to estimate diversity levels. We used spatially referenced trees ≥5 cm in diameter and simulated 0.10 ha plots measured from a 9 ha SDTF in southwestern Ecuador to compare machine learning (ML) models for six α-diversity indices. We developed 1 m tree canopy height and elevation models from stem mapped trees, at a scale conventionally derived from light detection and ranging (LiDAR). We then used an ensemble ML approach comparing single- and combined-sensor models from RapidEye, Sentinel-2 and interpolated canopy height and topography surfaces. Validation data showed that combined models often outperformed single-sensor approaches. Combined sensor and model ensembles for tree species richness, Shannon’s H, inverse Simpson’s, unbiased Simpson’s, and Fisher’s alpha indices typically showed lower root mean squared error (RMSE) and increased goodness of fit (R2). Piélou’s J, a measure of evenness, was poorly predicted. Mapped tree species richness (R2 = 0.54, F = 27.3, p = <0.001) and Shannon’s H′ (R2 = 0.54, F = 26.9, p = <0.001) showed the most favorable agreement with field validation observations (n = 25). Small-scale model experiments revealed essential relationships between dry forest tree diversity and data from multiple satellite sensors with repeated global coverage that can help guide larger-scale biodiversity mapping efforts.
An Energy Sensitive and Congestion Balance Routing Scheme for Non-Terrestrial-Satellite-Network (NTSN)
Authors: Jiang Yifei , Wu Shufan , Mo Qiankun , Liu Wenzheng , Wei Xiao
Published: January 2023

Recently, non-terrestrial-satellite-networks (NTSN) have attracted more attention due to excellent performance. NTSN specifically refers to a mega satellite constellation network. Global coverage, low latency and high data rate make global interconnection possible. However, the lack of on-board energy degrades the efficiency of the network system. To solve those pressing problems, an energy sensitive and congestion balance (ESCB) routing scheme is proposed in this paper. To compensate for the limited energy of satellites, a tubular sliding time window (TSTW) model is proposed. The residual energy can be predicted by it and a multi-objective algorithm is applied to calculate the routing path. Energy constraints, network congestion and latency are taken into account in the specific algorithm. A traffic model consisting of two different services is introduced as a verification system. Simulations demonstrate that the specific routing scheme achieves energy balance and congestion avoidance. In addition, comparison results demonstrate that ESCB is superior to the virtual-topology-based shortest path (VT-SP) routing algorithm.
Cotton Fiber Quality Estimation Based on Machine Learning Using Time Series UAV Remote Sensing Data
Authors: Xu Weicheng , Yang Weiguang , Chen Pengchao , Zhan Yilong , Zhang Lei , Lan Yubin
Published: January 2023

As an important factor determining the competitiveness of raw cotton, cotton fiber quality has received more and more attention. The results of traditional detection methods are accurate, but the sampling cost is high and has a hysteresis, which makes it difficult to measure cotton fiber quality parameters in real time and at a large scale. The purpose of this study is to use time-series UAV (Unmanned Aerial Vehicle) multispectral and RGB remote sensing images combined with machine learning to model four main quality indicators of cotton fibers. A deep learning algorithm is used to identify and extract cotton boll pixels in remote sensing images and improve the accuracy of quantitative extraction of spectral features. In order to simplify the input parameters of the model, the stepwise sensitivity analysis method is used to eliminate redundant variables and obtain the optimal input feature set. The results of this study show that the R2 of the prediction model established by a neural network is improved by 29.67% compared with the model established by linear regression. When the spectral index is calculated after removing the soil pixels used for prediction, R2 is improved by 4.01% compared with the ordinary method. The prediction model can well predict the average length, uniformity index, and micronaire value of the upper half. R2 is 0.8250, 0.8014, and 0.7722, respectively. This study provides a method to predict the cotton fiber quality in a large area without manual sampling, which provides a new idea for variety breeding and commercial decision-making in the cotton industry.
Impacts of Climate Change and Human Activities on NDVI in the Qinghai-Tibet Plateau
Authors: Sun Lu , Li Hao , Wang Jia , Chen Yuhan , Xiong Nina , Wang Zong , Wang Jing , Xu Jiangqi
Published: January 2023

Vegetation changes and factors have a profound influence on the local ecology, the economy, and the long-term durability of human construction. This study focuses on the impacts of climate change and human activity on vegetation changes on the Qinghai-Tibet Plateau and aims to develop a dataset of human activity levels on the plateau. Sen and Mann-Kendall trend analysis was used to evaluate the spatial distribution of vegetation NDVI and its trends, as well as the lagged response of plant growth to climatic circumstances. Using a geodetector model, the effects of meteorological and anthropogenic intensity data were examined. The study’s findings show that, although anthropogenic influences and ecosystem vulnerability caused a decline in the region’s vegetation, a stable climate and a healthy ecosystem supported the growth of vegetation. From 2000 to 2017, the area where vegetation grass improved significantly accounted for the highest proportion, reaching 34.22%. Different anthropogenic intensities are distributed spatially, and this interplay of anthropogenic intensities and climatic factors affects the distribution of vegetation greenness more than each element acting alone. The study of how human activity and climate change affect vegetation greenness can offer practical recommendations for maintaining the Qinghai-Tibet Plateau’s natural ecology. It is crucial to responsibly safeguard the Qinghai-Tibet Plateau’s environment in response to the nation’s ecological civilization.
Recursive RX with Extended Multi-Attribute Profiles for Hyperspectral Anomaly Detection
Authors: He Fang , Yan Shuai , Ding Yao , Sun Zhensheng , Zhao Jianwei , Hu Haojie , Zhu Yujie
Published: January 2023

Hyperspectral anomaly detection (HAD) plays an important role in military and civilian applications and has attracted a lot of research. The well-known Reed–Xiaoli (RX) algorithm is the benchmark of HAD methods. Based on the RX model, many variants have been developed. However, most of them ignore the spatial characteristics of hyperspectral images (HSIs). In this paper, we combine the extended multi-attribute profiles (EMAP) and RX algorithm to propose the Recursive RX with Extended Multi-Attribute Profiles (RRXEMAP) algorithm. Firstly, EMAP is utilized to extract the spatial structure information of HSI. Then, a simple method of background purification is proposed. That is, the background is purified by utilizing the RX detector to remove the pixels that are more likely to be anomalies, which helps improve the ability of background estimation. In addition, a parameter is utilized to control the purification level and can be selected by experiments. Finally, the RX detector is used again between the EMAP feature and the new background distribution to judge the anomaly. Experimental results on six real hyperspectral datasets and a synthetic dataset demonstrate the effectiveness of the proposed RRXEMAP method and the importance of using the EMAP feature and background purity means. Especially, on the abu-airport-2 dataset, the AUC value obtained by the present method is 0.9858, which is higher than the second one, CRD, by 0.0198.
The Creep-Sliding Deformation Mechanism of the Jiaju Ancient Landslide in the Upstream of Dadu River, Tibetan Plateau, China
Authors: Yan Yiqiu , Guo Changbao , Li Caihong , Yuan Hao , Qiu Zhendong
Published: January 2023

The Jiaju ancient landslide is a giant landslide located upstream of the Dadu River, eastern Tibetan Plateau, with a volume of approx. 7.04 × 108 m3. The Jiaju ancient landslide is complex and comprises five secondary sliding bodies, e.g., the Jiaju landslide (H01), Niexiaping landslide (H02), Xiaobawang landslide (H03), Niela landslide (H04), and Mt.-peak landslide (H05). Affected by regional neotectonic movement, heavy rainfall, river erosion, and lithology, the secondary sliding bodies of the Jiaju ancient landslide are undergoing significantly different creep-sliding deformation, which will cause great damage to villages, roads, and rivers around the sliding bodies. Combined with the SBAS-InSAR method, Sentinel-1A data from June 2018 to August 2021, remote sensing and field surveys, this study obtained the Jiaju ancient landslide deformation characteristics and deformation rate in the line-of-sight direction (VLOS), slope (VSlope), and vertical (VVertical). It is concluded that the maximum deformation rate of the Jiaju ancient landslide is significant. The maximum of VLOS, VSlope, and VVertical are −179 mm/a, −211 mm/a, and −67 mm/a, respectively. The Niela landslide (H04), Jiaju landslide (H01), and Mt.-peak landslide (H05) are very large and suffer strong deformation. Among these, the Niela landslide (H04) is in the accelerative deformation stage and at the Warn warning level, and the Jiaju landslide (H01) is in the creep deformation and attention warning level, especially heavy rainfall, which will accelerate landslide deformation and trigger reactivation. Because the geological structure is very complex for the Jiaju ancient landslide and strong neotectonic movement, under heavy rainfall, the secondary landslide creep-sliding rate of the Jiaju ancient landslide is easily accelerated and finally slides in part or as a whole, resulting in river blocking. It is suggested to strengthen the landslide deformation monitoring of the Niela landslide and Jiaju landslide and provide disaster mitigation and prevention support to the government and residents along the Dadu River watershed.
Focal Combo Loss for Improved Road Marking Extraction of Sparse Mobile LiDAR Scanning Point Cloud-Derived Images Using Convolutional Neural Networks
Authors: Lagahit Miguel Luis R. , Matsuoka Masashi
Published: January 2023

Road markings are reflective features on roads that provide important information for safe and smooth driving. With the rise of autonomous vehicles (AV), it is necessary to represent them digitally, such as in high-definition (HD) maps generated by mobile mapping systems (MMSs). Unfortunately, MMSs are expensive, paving the way for the use of low-cost alternatives such as low-cost light detection and ranging (LiDAR) sensors. However, low-cost LiDAR sensors produce sparser point clouds than their survey-grade counterparts. This significantly reduces the capabilities of existing deep learning techniques in automatically extracting road markings, such as using convolutional neural networks (CNNs) to classify point cloud-derived imagery. A solution would be to provide a more suitable loss function to guide the CNN model during training to improve predictions. In this work, we propose a modified loss function—focal combo loss—that enhances the capability of a CNN to extract road markings from sparse point cloud-derived images in terms of accuracy, reliability, and versatility. Our results show that focal combo loss outperforms existing loss functions and CNN methods in road marking extractions in all three aspects, achieving the highest mean F1-score and the lowest uncertainty for the two distinct CNN models tested.
Auto-Diagnosis of Time-of-Flight for Ultrasonic Signal Based on Defect Peaks Tracking Model
Authors: Yang Fan , Shi Dongliang , Lo Long-Yin , Mao Qian , Zhang Jiaming , Lam Kwok-Ho
Published: January 2023

With the popularization of humans working in tandem with robots and artificial intelligence (AI) by Industry 5.0, ultrasonic non-destructive testing (NDT)) technology has been increasingly used in quality inspections in the industry. As a crucial part of handling ultrasonic testing results–signal processing, the current approach focuses on professional training to perform signal discrimination but automatic and intelligent signal optimization and estimation lack systematic research. Though the automated and intelligent framework for ultrasonic echo signal processing has already exhibited essential research significance for diagnosing defect locations, the real-time applicability of the algorithm for the time-of-flight (ToF) estimation is rarely considered, which is a very important indicator for intelligent detection. This paper conducts a systematic comparison among different ToF algorithms for the first time and presents the auto-diagnosis of the ToF approach based on the Defect Peaks Tracking Model (DPTM). The proposed DPTM is used for ultrasonic echo signal processing and recognition for the first time. The DPTM using the Hilbert transform was verified to locate the defect with the size of 2–10 mm, in which the wavelet denoising method was adopted. With the designed mechanical fixture through 3D printing technology on the pipeline to inspect defects, the difficulty of collecting sufficient data could be conquered. The maximum auto-diagnosis error could be reduced to 0.25% and 1.25% for steel plate and pipeline under constant pressure, respectively, which were much smaller than those with the DPTM adopting the cross-correlation. The real-time auto-diagnosis identification feature of DPTM has the potential to be combined with AI in future work, such as machine learning and deep learning, to achieve more intelligent approaches for industrial health inspection.
A Review on Immune-Inspired Node Fault Detection in Wireless Sensor Networks with a Focus on the Danger Theory
Authors: Widhalm  Dominik , Goeschka  Karl M. , Kastner  Wolfgang
Published: January 2023

The use of fault detection and tolerance measures in wireless sensor networks is inevitable to ensure the reliability of the data sources. In this context, immune-inspired concepts offer suitable characteristics for developing lightweight fault detection systems, and previous works have shown promising results. In this article, we provide a literature review of immune-inspired fault detection approaches in sensor networks proposed in the last two decades. We discuss the unique properties of the human immune system and how the found approaches exploit them. With the information from the literature review extended with the findings of our previous works, we discuss the limitations of current approaches and consequent future research directions. We have found that immune-inspired techniques are well suited for lightweight fault detection, but there are still open questions concerning the effective and efficient use of those in sensor networks.
Dimethyl Carbonate as a Mobile-Phase Modifier for Normal-Phase and Hydrophilic Interaction Liquid Chromatography
Authors: Boes Philip D. , Elleman Sophie R. , Danielson Neil D.
Published: January 2023

We studied the use of dimethyl carbonate (DMC) as a non-toxic, aprotic modifier for hydrophilic liquid interaction chromatography (HILIC) and as a modifier for normal-phase liquid chromatography (LC). A comparison of ethyl acetate (EA) and DMC as organic mobile-phase modifiers in hexane for normal-phase LC of phthalates was conducted with a silica column and showed that retention factors (k) at the same modifier percentage were about a factor of two greater for DMC. Detection at 215 nm, possible with DMC, allowed for the better detection of the phthalates by a factor of 10, compared with EA detection, best at a 254 nm wavelength. Using a core-shell silica column, HILIC separations of trans-ferulic acid, syringic acid, and vanillic acid were compared between acetonitrile (MeCN) and DMC as the organic portion of the mobile phase, from 80–95%. The analyte retention for DMC, when compared to MeCN, was about 1.5 times greater, with only a moderate increase in back pressure. Plate count and peak asymmetry were somewhat better for the DMC chromatograms, compared to those with MeCN. Seven mono- and di-hydroxybenzoic acid positional isomers could be resolved effectively with DMC. Sorbate and benzoate preservatives in commercial drinks were also determined.
Application of a Small Protein-Coated Column to Trap, Extract and Enrich Carbamazepine Directly from Human Serum for Direct Chromatographic Analysis
Authors: Sonbol Heba , Ebrahim Hager , Malak Monika , Ali Ahmed , Aboulella Yasmine , Hadad Ghada , Emara Samy , Shawky Ahmed
Published: January 2023

An automated solid phase extraction (SPE) protocol to determine carbamazepine in human serum has been developed and validated using a simple, rabid and sensitive liquid chromatography-based bio-analytical method. Extraction of carbamazepine was carried out using an on-line SPE tool of a short protein-coated (PC) ODS silica pre-column (PC-ODS-pre-column) and phosphate buffer saline (PBS) with a pH of 7.4 as an extraction solvent. There are two distinct chromatographic modes used by PC-ODS-pre-column. While carbamazepine trapping required reversed-phase liquid chromatography, proteins were extracted from serum samples using PBS by size-exclusion liquid chromatography. Then, carbamazepine was eluted from the PC-ODS-pre-column onto the quantification position using a mixture of methanol-distilled deionized water (50:50, v/v) as an eluent and ODS analytical column. At room temperature (22 ± 1 °C), carbamazepine was completely separated from the co-eluted matrix components and detected at 230 nm. Carbamazepine’s linearity was obtained at concentrations ranging from 50 to 10,000 ng/mL. With good accuracy and precision, carbamazepine recoveries in serum samples ranged from 86.14 to 97.82%. The extraction step was conducted using PBS as a safe and green extraction solvent, making this protocol both cost-effective and ecologically safe.
Anti-Inflammatory, Anti-Oxidant, GC-MS Profiling and Molecular Docking Analyses of Non-Polar Extracts from Five Salsola Species
Authors: Elwekeel Ahlam , Hassan Marwa , Almutairi Ebtihaj , AlHammad Maryam , Alwhbi Farah , Abdel-Bakky Mohamed , Amin Elham , Mohamed Enas
Published: January 2023

Genus Salsola (family Amaranthaceae) is one of the most prevailing genera in Saudi Arabia. Although several species were reported for their traditional uses, the majority of Salsola species still need to be phytochemically and biologically explored. The current study presents the GC-MS profiling as well as an in vitro investigation of the bioactivities of the n-hexane extracts from the five Salsola species: Salsola arabica, S. cyclophylla, S. imbricata, S. incanescens and S. villosa. Additionally, the compounds identified in the most active extracts were screened for their interaction with the active sites of cyclooxygenase enzyme isoforms (COX-1 and COX-2). GC-MS analysis of the n-hexane extracts from the five species resulted in the identification of 67 constituents. Oleic acid (75.57%), 1-octadecene (14.46%), cinnamaldehyde α-hexyl (57.15%), octacosyl heptafluorobutyrate (25.36%) and hexadecanoic acid methyl ester (26.15%) represent the major constituents in S. arabica, S. cyclophylla, S. imbricata, S. inscanescence and S. villosa, respectively. Results of bioactivity testing highlighted S. villosa as having the highest anti-oxidant activity (IC50 0.99 ± 0.05 mg/mL), which was closely followed by S. cyclophylla (IC50 1.36 ± 0.06 mg/mL) compared to the IC50 of 0.16 ± 0.01 mg/mL recorded by ascorbic acid. S. villosa was further noted for having the strongest COX-2 inhibitory activity (IC50 4.6 ± 0.13 µg/mL) among the tested extracts followed by S. arabica (IC50 13.1 ± 0.37 µg/mL) and S. cyclophylla (IC50 20.1 ± 0.57 µg/mL). On the other hand, S. imbricata extract displayed the most characteristic inhibition activity against COX-1 (IC50 10.2 ± 0.52 µg/mL), which was non-significant from the standard drug celecoxib. Based upon bioactivity results, the phytoconstituents identified in S. villosa and S. imbricata extracts were investigated for their capability to interact with the active sites of both cyclooxygenase enzyme isoforms adopting molecular docking. Results indicated the possibility to incorporate the compounds to active sites of the enzymes where some of them bind with their polar end into the cavity beyond Arg120 and their aliphatic chain oriented to the catalytically important Tyr385 similar to the natural substrate arachidonic acid, indicating that they could be promising candidates for the future development of selective COX inhibitors.
Helping or Controlling? Choice of Coping Methods When Dealing with Violent Clients in Statutory Social Work
Authors: Munobwa Jimmy Stephen , Öberg Peter , Ahmadi Fereshteh
Published: January 2023

Client violence in social work is a workplace problem in Sweden and internationally. Frontline workers in public agencies have the discretion to decide how they deal with clients to cope with challenges like violence and threats. The coping methods may favour some clients while disadvantaging others. Ultimately, the coping practices may become de facto policy, which may not match official organisational policy. This article explores coping methods statutory social workers use to manage violence and threats in their day-to-day dyadic interactions with clients. The article is based on qualitative interviews with social workers (n = 19) who, according to their perception, were victims of client violence. Theory on street-level bureaucracy and frontline workers’ discretion is used. Based on thematic analysis, the results show that social workers draw from four groups of coping methods depending on their moral and normative dispositions. These include (1) the forced helper, (2) the compassionate helper, (3) the distanced helper, and (4) the authoritarian helper. Social workers oscillate between different dispositions depending on situational needs, striving to find the appropriate balance between helping and controlling clients. Studying social workers’ day-to-day dyadic interactions with clients highlights how coping methods could shape social work policy and practice.
Urban Heat Island’s Vulnerability Assessment by Integrating Urban Planning Policies: A Case Study of Montpellier Méditerranée Metropolitan Area, France
Authors: Técher Magalie , Ait Haddou Hassan , Aguejdad Rahim
Published: January 2023

The energy balance differences between urban and rural areas give rise to a representative phenomenon of urban climate change called the urban heat island (UHI). The UHI phenomenon, which is exacerbated by global warming effects and urban expansion, exposes urban areas and populations to thermal stress and overheating. Therefore, measuring the intensity of UHI vulnerability is needed to mitigate its effects on health, comfort, energy consumption and infrastructure. Additionally, urban decision makers are looking for methodologies to identify the most vulnerable areas in urban planning. This research aims to investigate areas prone to urban overheating in Montpellier Mediterranean metropolitan area as a representative case study of the French urban planning context. The objective is to develop a methodology for assessing UHI vulnerability based on the interaction of exposure and sensitivity to urban planning policies. Accordingly, a set of fifteen indicators is developed to visualize urban planning policies, exposure and sensitivity to urban overheating. A statistical-based method is applied to determine the individual weights based on the indicators’ variance, which is calculated using principal component analysis (PCA). The spatial and urban planning distribution of vulnerability is then analyzed. The results indicate that the areas with the highest urban planning challenges are most vulnerable to UHI. In fact, the results reveal that these areas have urban planning characteristics likely to aggravate urban overheating. Therefore, this research proposes a methodology for integrating mitigation solutions into urban planning: increase in permeable and green areas; improvement of urban ventilation and heat exchange and decrease in anthropogenic heat generation. It demonstrates that combining urban planning policies with exposure and sensitivity is a new perspective for vulnerability studies. The findings of this study can be utilized by decision makers to better visualize areas susceptible to UHI and plan appropriate mitigation strategies.
The Role of Informal Waste Management in Urban Metabolism: A Review of Eight Latin American Countries
Authors: Espinosa-Aquino Beatriz , Gabarrell Durany Xavier , Quirós Vargas Roberto
Published: January 2023

Social and spatial segregation structures in Latin America are perceived as processes for the selective concentration of social or demographic groups in geographic sectors of the city. This voluntary or forced segregation creates poor, wealthy, and marginal areas, leading to the territory’s marginalization and fragmentation, destroying the symbolic and territorial urban continuity. To understand the behavior of waste pickers in a Mexican city, we sought to know the conditions of the informal collection activity in eight Latin American countries with similar conditions. Therefore, the goal was to carry out a bibliographic evaluation that included the environmental contribution of waste pickers, their organizations, and their link with urban metabolism. The tasks performed by informal waste pickers in the cities of the eight selected Latin American countries, their organizations, and their way of working were studied. Their role in reducing environmental impact and improving the quality of life of city dwellers was evaluated. Web sites, web searches, and face-to-face meetings created electronic communication channels with this community were analyzed. In some cases, they are well organized and become microentrepreneurs with salary, social security, and economical insurance by starting an ecological business. In contrast, marginal groups seeking economic support collect, separate, sort, and group recoverable waste daily and sell it at waste distribution points. This link in the urban metabolism reintroduces valuable solid waste into the production chain. In addition, materials with commercial value, such as metals, plastics, paper, cardboard, and wood, can re-enter the production chain as secondary materials for industry. Thus, a collective of well-organized waste pickers contributes to the city’s sustainability and provides better living conditions for the waste pickers. In Mexico, there is a lack of official information regarding the number of waste pickers, organizations, activities, and their environmental contribution. Therefore, a directory with that information is highly relevant to designing public policies to recognize the essential contributions of this sector.