bluuebunny/crossref_metadata_2025 huggingface dataset:
Dairy Consumption and Risk of Metabolic Syndrome: Results from Korean Population and Meta-Analysis
Authors: Jin Shaoyue , Je Youjin
Published: May 2021

Dairy consumption has been associated with decreased risk of metabolic syndrome (MetS) in previous studies, but the association may be different according to each type of dairy products and its subgroups. Thus, we conducted an updated meta-analysis of observational studies to examine the association between various dairy products and risk of MetS. The PubMed and Web of Science databases were searched for eligible studies published up to February 2021. In addition, we included unpublished results from Korea National Health and Nutrition Examination Survey, 2013–2018, including 23,319 Korean adults and the elderly. A total of 35 studies (12 cohort studies and 25 cross-sectional studies) with 398,877 subjects were included in the meta-analysis. The pooled relative risks (RR) of MetS for the highest versus lowest categories of dairy consumption was 0.80 [95% confidence interval (CI): 0.72–0.88]. For the type of dairy products, there were also significant inverse associations with milk (RR: 0.83; 95% CI: 0.78–0.89) and yogurt consumption (RR: 0.89; 95% CI: 0.83–0.95). For cheese consumption, however, no significant association was found (RR: 0.98; 95% CI: 0.86–1.11). Our findings suggest that milk and yogurt consumption is inversely associated with the risk of MetS, but not cheese consumption.
High and Low Haemoglobin Levels in Early Pregnancy Are Associated to a Higher Risk of Miscarriage: A Population-Based Cohort Study
Authors: Díaz-López Andrés , Ribot Blanca , Basora Josep , Arija Victoria
Published: May 2021

To evaluate whether women with anaemia or high haemoglobin (Hb) in early pregnancy would be at higher risk of miscarriage, this population-based cohort study involved 9453 women whose pregnancies were monitored at primary care centres between 2007 and 2012. The computerised clinical histories were used to collect: Hb measurements (up to 14 weeks of gestation), miscarriage before or by 24 weeks of gestation, and other maternal characteristics. The relation between anaemia (Hb < 110 g/L), normal Hb (110–140 g/L, reference), and high Hb concentrations (≥140 g/L) with miscarriage were expressed as adjusted OR with 95%CI. Restricted cubic spline models were applied to evaluate the dose-response relationships. A total of 520 (5.5%) women were recorded as having a miscarriage. The rate of miscarriage in anaemia, normal Hb, and high Hb concentrations was 8.4%, 5.1%, and 10.2%, respectively. Compared with women with normal Hb at the first trimester, the multivariable-adjusted OR for miscarriage was 2.11 (95%CI, 1.38–3.21) for women with anaemia and 1.83 (95%CI, 1.29–2.58) for women with high Hb. Hb concentrations showed a U-shaped association with miscarriage, with the lowest incidence among women with Hb of 120–130 g/L. These data highlight the importance of considering anaemia and high Hb levels in early pregnancy as harmful indicators for miscarriage.
Dietary Data in the Malmö Offspring Study–Reproducibility, Method Comparison and Validation against Objective Biomarkers
Authors: Hellstrand Sophie , Ottosson Filip , Smith Einar , Brunkwall Louise , Ramne Stina , Sonestedt Emily , Nilsson Peter M. , Melander Olle , Orho-Melander Marju , Ericson Ulrika
Published: May 2021

Irregular dietary intakes impairs estimations from food records. Biomarkers and method combinations can be used to improve estimates. Our aim was to examine reproducibility from two assessment methods, compare them, and validate intakes against objective biomarkers. We used the Malmö Offspring Study (55% women, 18–71 y) with data from a 4-day food record (4DFR) and a short food frequency questionnaire (SFFQ) to compare (1) repeated intakes (n = 180), (2) intakes from 4DFR and SFFQ (n = 1601), and (3) intakes of fatty fish, fruits and vegetables, and citrus with plasma biomarkers (n = 1433) (3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid [CMPF], β-carotene and proline betaine). We also combined 4DFR and SFFQ estimates using principal component analysis (PCA). Moderate correlations were seen between repeated intakes (4DFR median ρ = 0.41, SFFQ median ρ = 0.59) although lower for specific 4DFR-items, especially fatty/lean fish (ρ ≤ 0.08). Between-method correlations (median ρ = 0.33) were higher for intakes of overall food groups compared to specific foods. PCA scores for citrus (proline betaine ρ = 0.53) and fruits and vegetables (β-carotene: ρ = 0.39) showed the highest biomarker correlations, whereas fatty fish intake from the SFFQ per se showed the highest correlation with CMPF (ρ = 0.46). To conclude, the reproducibility of SFFQ data was superior to 4DFR data regarding irregularly consumed foods. Method combination could slightly improve fruit and vegetable estimates, whereas SFFQ data gave most valid fatty fish intake.
Serological Evidence of Human Orthohantavirus Infections in Barbados, 2008 to 2016
Authors: Douglas Kirk Osmond , Samuels Thelma Alafia , Iheozor-Ejiofor Rommel , Vapalahti Olli , Sironen Tarja , Gittens-St. Hilaire Marquita
Published: May 2021

Background: Hantavirus pulmonary syndrome (HPS) is well-known in South and North America; however, not enough data exist for the Caribbean. The first report of clinical orthohantavirus infection was obtained in Barbados, but no other evidence of clinical orthohantavirus infections among adults in the Caribbean has been documented. Methods: Using enzyme linked immunosorbent assay (ELISA) tests followed by confirmatory testing with immunofluorescent assays (IFA), immunochromatographic (ICG) tests, and pseudotype focus reduction neutralization tests (pFRNT), we retrospectively and prospectively detected orthohantavirus-specific antibodies among patients with febrile illness in Barbados. Results: The orthohantavirus prevalence rate varied from 5.8 to 102.6 cases per 100,000 persons among febrile patients who sought medical attention annually between 2008 and 2016. Two major orthohantavirus epidemics occurred in Barbados during 2010 and 2016. Peak orthohantavis infections were observed observed during the rainy season (August) and prevalence rates were significantly higher in females than males and in patients from urban parishes than rural parishes. Conclusions: Orthohantavirus infections are still occurring in Barbados and in some patients along with multiple pathogen infections (CHIKV, ZIKV, DENV and Leptospira). Orthohantavirus infections are more prevalent during periods of high rainfall (rainy season) with peak transmission in August; females are more likely to be infected than males and infections are more likely among patients from urban rather than rural parishes in Barbados.
The Synthesis and Evaluation of Multivalent Glycopeptoids as Inhibitors of the Adhesion of Candida albicans
Authors: Martin Harlei , Masterson Hannah , Kavanagh Kevin , Velasco-Torrijos Trinidad
Published: May 2021

Multivalency is a strategy commonly used by medicinal carbohydrate chemists to increase the affinity of carbohydrate-based small molecules for their protein targets. Although this approach has been very successful in enhancing binding to isolated carbohydrate-binding proteins, anticipating the multivalent presentations that will improve biological activity in cellular assays remains challenging. In this work we investigate linear molecular scaffolds for the synthesis of a low valency presentation of a divalent galactoside 1, previously identified by us as an inhibitor of the adhesion of opportunistic fungal pathogen Candida albicans to buccal epithelial cells (BECs). Adhesion inhibition assays revealed that multivalent glycoconjugate 3 is more effective at blocking C. albicans adherence to BECs upon initial exposure to epithelial cells. Interestingly, 3 did not seem to have any effect when it was pre-incubated with yeast cells, in contrast to the original lead compound 1, which caused a 25% reduction of adhesion. In competition assays, where yeast cells and BECs were co-incubated, multivalent glycoconjugate 3 inhibited up to 49% C. albicans adherence in a dose-dependent manner. The combined effect of compound 1 towards both yeast cells and BECs allowed it to achieve over 60% inhibition of the adhesion of C. albicans to BECs in competition assays.
Molecular Epidemiological Study of Hand, Foot, and Mouth Disease in a Kindergarten-Based Setting in Bangkok, Thailand
Authors: Thammasonthijarern Nipa , Kosoltanapiwat Nathamon , Nuprasert Warisa , Sittikul Pichamon , Sriburin Pimolpachr , Pan-ngum Wirichada , Maneekan Pannamas , Hataiyusuk Somboon , Hattasingh Weerawan , Thaipadungpanit Janjira , Chatchen Supawat
Published: May 2021

Hand, foot, and mouth disease (HFMD) is a contagious childhood illness and annually affects millions of children aged less than 5 years across the Asia–Pacific region. HFMD transmission mainly occurs through direct contact (person-to-person) and indirect contact with contaminated surfaces and objects. Therefore, public health measures to reduce the spread of HFMD in kindergartens and daycare centers are essential. Based on the guidelines by the Department of Disease Control, a school closure policy for HFMD outbreaks wherein every school in Thailand must close when several HFMD classrooms (more than two cases in each classroom) are encountered within a week, was implemented, although without strong supporting evidence. We therefore conducted a prospective cohort study of children attending five kindergartens during 2019 and 2020. We used molecular genetic techniques to investigate the characteristics of the spreading patterns of HFMD in a school-based setting in Bangkok, Thailand. These analyses identified 22 index cases of HFMD (symptomatic infections) and 25 cases of enterovirus-positive asymptomatic contacts (24 students and one teacher). Enterovirus (EV) A71 was the most common enterovirus detected, and most of the infected persons (8/12) developed symptoms. Other enteroviruses included coxsackieviruses (CVs) A4, CV-A6, CV-A9, and CV-A10 as well as echovirus. The pattern of the spread of HFMD showed that 45% of the subsequent enteroviruses detected in each outbreak possessed the same serotype as the first index case. Moreover, we found a phylogenetic relationship among enteroviruses detected among contact and index cases in the same kindergarten. These findings confirm the benefit of molecular genetic assays to acquire accurate data to support school closure policies designed to control HFMD infections.
Current Prospects for Treatment of Solid Tumors via Photodynamic, Photothermal, or Ionizing Radiation Therapies Combined with Immune Checkpoint Inhibition (A Review)
Authors: Anand Sanjay , Chan Timothy , Hasan Tayyaba , Maytin Edward
Published: May 2021

Photodynamic therapy (PDT) causes selective damage to tumor cells and vasculature and also triggers an anti-tumor immune response. The latter fact has prompted the exploration of PDT as an immune-stimulatory adjuvant. PDT is not the only cancer treatment that relies on electromagnetic energy to destroy cancer tissue. Ionizing radiation therapy (RT) and photothermal therapy (PTT) are two other treatment modalities that employ photons (with wavelengths either shorter or longer than PDT, respectively) and also cause tissue damage and immunomodulation. Research on the three modalities has occurred in different “silos”, with minimal interaction between the three topics. This is happening at a time when immune checkpoint inhibition (ICI), another focus of intense research and clinical development, has opened exciting possibilities for combining PDT, PTT, or RT with ICI to achieve improved therapeutic benefits. In this review, we surveyed the literature for studies that describe changes in anti-tumor immunity following the administration of PDT, PTT, and RT, including efforts to combine each modality with ICI. This information, collected all in one place, may make it easier to recognize similarities and differences and help to identify new mechanistic hypotheses toward the goal of achieving optimized combinations and tumor cures.
A Path Forward: Promoting Microbial-Based Methods in the Control of Invasive Plant Species
Authors: Shahrtash Maryam , Brown Shawn P.
Published: May 2021

In this review, we discuss the unrealized potential of incorporating plant–microbe and microbe–microbe interactions into invasive plant management strategies. While the development of this as a viable strategy is in its infancy, we argue that incorporation of microbial components into management plans should be a priority and has great potential for diversifying sustainable control options. We advocate for increased research into microbial-mediated phytochemical production, microbial controls to reduce the competitiveness of invasive plants, microbial-mediated increases of herbicidal tolerance of native plants, and to facilitate increased pathogenicity of plant pathogens of invasive plants.
Soil Properties and Weed Dynamics in Wheat as Affected by Rice Residue Management in the Rice–Wheat Cropping System in South Asia: A Review
Authors: Kaur Ramanpreet , Kaur Simerjeet , Deol Jasdev Singh , Sharma Rajni , Kaur Tarundeep , Brar Ajmer Singh , Choudhary Om Parkash
Published: May 2021

The rice–wheat cropping system (RWCS) has substantially contributed in making India self-sufficient in food grain production; however, rice residue management is of great concern, threatening the sustainability of this system. Rice residue is invariably disposed of by farmers through open burning. In addition to environmental pollution, residue burning of rice also leads to loss of soil nutrients. One of the alternatives to overcome these problems and sustain the RWCS is managing the rice residues in the field itself. Rice residue retention has variable effects on agricultural pests (namely, weeds, insect pests, diseases, and rodents) in the RWCS. High weed infestation in the RWCS results in high consumption of herbicides, which leads to several ecological problems and evolution of herbicide resistance. The shift from intensive tillage to conservation tillage causes major changes in weed dynamics and herbicide efficacy. Incorporation of rice residue reduces weed density and helps in improving soil physical, chemical, and biological properties. Rice residue retention on the surface or mulching reduces weed density and the biomass of both grass and broadleaf weeds in wheat crop as compared to its removal. Long-term field studies involving the use of rice residue as a component of integrated weed management strategies are needed to be done in the RWCS.
Cowpea Crop Response to Mineral and Organic Fertilization in SE Spain
Authors: Sánchez-Navarro Virginia , Zornoza Raúl , Faz Ángel , Fernández Juan Antonio
Published: May 2021

Mineral fertilization is considered to be useful for improving soil fertility and yields. However, its use is linked to global warming and soil and water pollution by its rapid mobilization. On the other hand, organic fertilization is recommended to maintain or improve soil organic carbon and total nitrogen stocks while contributing to climate change mitigation. The main goal of this study was to assess the effect of two different fertilizer types, mineral and organic, during three cowpea crop cycles on the soil’s physicochemical properties, enzyme activities, crop yield, crop quality and nutritional composition when considering two cowpea cultivars (Feijão frade de fio preto (FP) and Feijão frade de fio claro (FC)). The use of mineral fertilizers was seen to contribute to improved soil fertility due to the increase in soil properties, such as recalcitrant carbon, total nitrogen, ammonium content, available K and available Mg. On the other hand, organic fertilizers only increased the nitrate content in the soil. There were no differences in terms of cowpea crop yield, quality and nutritional composition by fertilizer type. Thus, both fertilizer types contributed to the same crop yield and quality, and thus the use of organic fertilizers can result in a sustainable alternative for maintaining cowpea crop yield and quality.
Polyphenolic Profiling of Green Waste Determined by UPLC-HDMSE
Authors: Potter Colin M. , Jones David L.
Published: May 2021

Valorising green waste will greatly enhance and promote the sustainable management of this large volume resource. One potential way to achieve this is the extraction of high value human health promoting chemicals (e.g., polyphenols) from this material. Our primary aim was to identify the main polyphenols present in four contrasting green waste feedstocks, namely Smyrnium olusatrum, Urtica dioica, Allium ursinum and Ulex europaeus, using UPLC-HDMSE. Polyphenol-rich Camellia sinensis (green tea) was used as a reference material. Samples were extracted and analysed by UPLC-HDMSE, which was followed by data processing using Progenesis QI and EZ Info. A total of 77 high scoring polyphenolic compounds with reported benefits to human health were tentatively identified in the samples, with abundances varying across the plant types; A. ursinum was seen to be the least abundant in respect to the polyphenols identified, whereas U. europaeus was the most abundant. Important components with a diverse range of bioactivity, such as procyanidins, (−)-epigallocatechin, naringenin, eriodictyol and iso-liquiritigenin, were observed, plus a number of phytoestrogens such as daidzein, glycitin and genistein. This research provides a route to valorise green waste through the creation of nutritional supplements which may aid in the prevention of disease.
Simulation Study of Utilizing X-ray Tube in Monitoring Systems of Liquid Petroleum Products
Authors: Roshani Gholam Hossein , Ali Peshawa Jammal Muhammad , Mohammed Shivan , Hanus Robert , Abdulkareem Lokman , Alanezi Adnan Alhathal , Sattari Mohammad Amir , Amiri Saba , Nazemi Ehsan , Eftekhari-Zadeh Ehsan , Kalmoun El Mostafa
Published: May 2021

Radiation-based instruments have been widely used in petrochemical and oil industries to monitor liquid products transported through the same pipeline. Different radioactive gamma-ray emitter sources are typically used as radiation generators in the instruments mentioned above. The idea at the basis of this research is to investigate the use of an X-ray tube rather than a radioisotope source as an X-ray generator: This choice brings some advantages that will be discussed. The study is performed through a Monte Carlo simulation and artificial intelligence. Here, the system is composed of an X-ray tube, a pipe including fluid, and a NaI detector. Two-by-two mixtures of four various oil products with different volume ratios were considered to model the pipe’s interface region. For each combination, the X-ray spectrum was recorded in the detector in all the simulations. The recorded spectra were used for training and testing the multilayer perceptron (MLP) models. After training, MLP neural networks could estimate each oil product’s volume ratio with a mean absolute error of 2.72 which is slightly even better than what was obtained in former studies using radioisotope sources.
A Study on Standardization of Security Evaluation Information for Chemical Processes Based on Deep Learning
Authors: Peng Lanfei , Gao Dong , Bai Yujie
Published: May 2021

Hazard and operability analysis (HAZOP) is one of the most commonly used hazard analysis methods in the petrochemical industry. The large amount of unstructured data in HAZOP reports has generated an information explosion which has led to a pressing need for technologies that can simplify the use of this information. In order to solve the problem that massive data are difficult to reuse and share, in this study, we propose a new deep learning framework for Chinese HAZOP documents to perform a named entity recognition (NER) task, aiming at the characteristics of HAZOP documents, such as polysemy, multi-entity nesting, and long-distance text. Specifically, the preprocessed data are input into an embeddings from language models (ELMo) and a double convolutional neural network (DCNN) model to extract rich character features. Meanwhile, a bidirectional long short-term memory (BiLSTM) network is used to extract long-distance semantic information. Finally, the results are decoded by a conditional random field (CRF), and then output. Experiments were carried out using the HAZOP report of a coal seam indirect liquefaction project. The experimental results for the proposed model showed that the accuracy rate of the optimal results reached 90.83, the recall rate reached 92.46, and the F-value reached the highest 91.76%, which was significantly improved as compared with other models.
Static Behaviors and Applications of Buckling Monitoring Members with Rigid Ends
Authors: Ying Wudang , Deng Changgen , Zhang Chenhui
Published: May 2021

The buckling of compression members may lead to the progressive collapse of spatial structures. Based on the sleeved compression member, the buckling monitoring member is introduced to control the buckling of compression member and raise buckling alert by sensing contact between the core tube and the restraining tube. Considering the rigid connection among the members in spatial structures, the buckling monitoring member with rigid ends needs to be further analyzed. An experimental test was conducted and finite element analyses were performed with calibrated finite element models. The results indicated that the ultimate bearing capacity and post-ultimate bearing capacity of the core tube were enhanced due to the restraint from the restraining tube. The contact was successfully sensed by pressure sensor, revealing that it sensed the buckling of the core tube. Parametric studies were conducted, indicating that the core protrusion, core slenderness ratio, the gap between the core tube and restraining tube, and the flexural rigidity ratio are the key parameters affecting the bearing capacity and the failure modes of the buckling monitoring member, and some key values of parameters were proposed to obtain good bearing capacity. Based on the parametric studies, the failure modes of buckling-monitoring members are summarized as global buckling and local buckling. The stress distribution and deformation mode of buckling monitoring members are presented in the non-contact, point-contact, line-contact, reverse-contact and ultimate bearing state. The buckling monitoring member is applied in a reticulated shell by substituting the buckling members. It can effectively improve the ultimate bearing capacity of reticulated shell.
Multi-Criteria Analysis of Smart Cities on the Example of the Polish Cities
Authors: Hajduk Sławomira
Published: May 2021

This paper presents the application of a Multi-Criteria Decision Making (MCDM) method for the ranking of smart cities. During the construction of the MCDM techniques, the importance of the decision-making approach for the linear ordering of 66 Polish cities with powiat status was presented. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used for evaluation. The method has been verified by applying it to measure urban smartness. The TOPSIS method allowed compilation for a final ranking, taking into account publicly available indicators of the smart cities concept. The work uses data from the Local Data Bank Polish Central Statistical Office (LDB). The author conducted a literature review of research papers related to smart cities and MCDM methods dated from 2010 to 2020. Based on calculations using the TOPSIS method, the results obtained that the city of Krakow has the highest value to become a smart city.
Predicting Height to Crown Base of Larix olgensis in Northeast China Using UAV-LiDAR Data and Nonlinear Mixed Effects Models
Authors: Liu Xin , Hao Yuanshuo , Widagdo Faris Rafi Almay , Xie Longfei , Dong Lihu , Li Fengri
Published: May 2021

As a core content of forest management, the height to crown base (HCB) model can provide a theoretical basis for the study of forest growth and yield. In this study, 8364 trees of Larix olgensis within 118 sample plots from 11 sites were measured to establish a two-level nonlinear mixed effect (NLME) HCB model. All predictors were derived from an unmanned aerial vehicle light detection and ranging (UAV-LiDAR) laser scanning system, which is reliable for extensive forest measurement. The effects of the different individual trees, stand factors, and their combinations on the HCB were analyzed, and the leave-one-site-out cross-validation was utilized for model validation. The results showed that the NLME model significantly improved the prediction accuracy compared to the base model, with a mean absolute error and relative mean absolute error of 0.89% and 9.71%, respectively. In addition, both site-level and plot-level sampling strategies were simulated for NLME model calibration. According to different prediction scale and accuracy requirements, selecting 15 trees randomly per site or selecting the three largest trees and three medium-size trees per plot was considered the most favorable option, especially when both investigations cost and the model’s accuracy are primarily considered. The newly established HCB model will provide valuable tools to effectively utilize the UAV-LiDAR data for facilitating decision making in larch plantations management.
Unpaired Underwater Image Synthesis with a Disentangled Representation for Underwater Depth Map Prediction
Authors: Zhao Qi , Xin Zhichao , Yu Zhibin , Zheng Bing
Published: May 2021

As one of the key requirements for underwater exploration, underwater depth map estimation is of great importance in underwater vision research. Although significant progress has been achieved in the fields of image-to-image translation and depth map estimation, a gap between normal depth map estimation and underwater depth map estimation still remains. Additionally, it is a great challenge to build a mapping function that converts a single underwater image into an underwater depth map due to the lack of paired data. Moreover, the ever-changing underwater environment further intensifies the difficulty of finding an optimal mapping solution. To eliminate these bottlenecks, we developed a novel image-to-image framework for underwater image synthesis and depth map estimation in underwater conditions. For the problem of the lack of paired data, by translating hazy in-air images (with a depth map) into underwater images, we initially obtained a paired dataset of underwater images and corresponding depth maps. To enrich our synthesized underwater dataset, we further translated hazy in-air images into a series of continuously changing underwater images with a specified style. For the depth map estimation, we included a coarse-to-fine network to provide a precise depth map estimation result. We evaluated the efficiency of our framework for a real underwater RGB-D dataset. The experimental results show that our method can provide a diversity of underwater images and the best depth map estimation precision.
Automatic vs. Human Recognition of Pain Intensity from Facial Expression on the X-ITE Pain Database
Authors: Othman Ehsan , Werner Philipp , Saxen Frerk , Al-Hamadi Ayoub , Gruss Sascha , Walter Steffen
Published: May 2021

Prior work on automated methods demonstrated that it is possible to recognize pain intensity from frontal faces in videos, while there is an assumption that humans are very adept at this task compared to machines. In this paper, we investigate whether such an assumption is correct by comparing the results achieved by two human observers with the results achieved by a Random Forest classifier (RFc) baseline model (called RFc-BL) and by three proposed automated models. The first proposed model is a Random Forest classifying descriptors of Action Unit (AU) time series; the second is a modified MobileNetV2 CNN classifying face images that combine three points in time; and the third is a custom deep network combining two CNN branches using the same input as for MobileNetV2 plus knowledge of the RFc. We conduct experiments with X-ITE phasic pain database, which comprises videotaped responses to heat and electrical pain stimuli, each of three intensities. Distinguishing these six stimulation types plus no stimulation was the main 7-class classification task for the human observers and automated approaches. Further, we conducted reduced 5-class and 3-class classification experiments, applied Multi-task learning, and a newly suggested sample weighting method. Experimental results show that the pain assessments of the human observers are significantly better than guessing and perform better than the automatic baseline approach (RFc-BL) by about 1%; however, the human performance is quite poor due to the challenge that pain that is ethically allowed to be induced in experimental studies often does not show up in facial reaction. We discovered that downweighting those samples during training improves the performance for all samples. The proposed RFc and two-CNNs models (using the proposed sample weighting) significantly outperformed the human observer by about 6% and 7%, respectively.
Linear Matrix Inequalities for an Iterative Solution of Robust Output Feedback Control of Systems with Bounded and Stochastic Uncertainty
Authors: Rauh Andreas , Romig Swantje
Published: May 2021

Linear matrix inequalities (LMIs) have gained much importance in recent years for the design of robust controllers for linear dynamic systems, for the design of state observers, as well as for the optimization of both. Typical performance criteria that are considered in these cases are either H2 or H∞ measures. In addition to bounded parameter uncertainty, included in the LMI-based design by means of polytopic uncertainty representations, the recent work of the authors showed that state observers can be optimized with the help of LMIs so that their error dynamics become insensitive against stochastic noise. However, the joint optimization of the parameters of the output feedback controllers of a proportional-differentiating type with a simultaneous optimization of linear output filters for smoothening measurements and for their numeric differentiation has not yet been considered. This is challenging due to the fact that the joint consideration of both types of uncertainties, as well as the combined control and filter optimization lead to a problem that is constrained by nonlinear matrix inequalities. In the current paper, a novel iterative LMI-based procedure is presented for the solution of this optimization task. Finally, an illustrating example is presented to compare the new parameterization scheme for the output feedback controller—which was jointly optimized with a linear derivative estimator—with a heuristically tuned D-type control law of previous work that was implemented with the help of an optimized full-order state observer.
Tilted-Beam Antenna Based on SSPPs-TL with Stable Gain
Authors: Wei Dujuan , Geng Youlin , Zhang Pengquan , Zhang Zhonghai , Yin Chuan
Published: May 2021

In this paper, a titled-beam antenna based on spoof surface plasmon polaritons (SSPPs) transmission lines (TLs) is proposed. The parallel SSPPs-TL is a slow-wave TL, which is able to limit waves in the TL strictly. By periodically introducing a set of tapered stubs along the SSPPs-TL, the backward endfire beams are formed by the surface waves in the slow-wave radiation region. Then, through the placement of a big metal plate below the endfire antenna, the backward endfire beams are tilted, and the tilted angle of the beams are steered by the distance of the metal plate and antenna. Over the band of 5.7 GHz~7.0 GHz, the tilted antenna performs constant shapes of radiation patterns. The gain keeps stable at around 12 dBi and the 1-dB gain bandwidth is 20%. The measured results of the fabricated prototypes confirm the design theory and simulated results.
Relevance of Drift Components and Unit-to-Unit Variability in the Predictive Maintenance of Low-Cost Electrochemical Sensor Systems in Air Quality Monitoring
Authors: Tancev Georgi
Published: May 2021

As key components of low-cost sensor systems in air quality monitoring, electrochemical gas sensors have recently received a lot of interest but suffer from unit-to-unit variability and different drift components such as aging and concept drift, depending on the calibration approach. Magnitudes of drift can vary across sensors of the same type, and uniform recalibration intervals might lead to insufficient performance for some sensors. This publication evaluates the opportunity to perform predictive maintenance solely by the use of calibration data, thereby detecting the optimal moment for recalibration and improving recalibration intervals and measurement results. Specifically, the idea is to define confidence regions around the calibration data and to monitor the relative position of incoming sensor signals during operation. The emphasis lies on four algorithms from unsupervised anomaly detection—namely, robust covariance, local outlier factor, one-class support vector machine, and isolation forest. Moreover, the behavior of unit-to-unit variability and various drift components on the performance of the algorithms is discussed by analyzing published field experiments and by performing Monte Carlo simulations based on sensing and aging models. Although unsupervised anomaly detection on calibration data can disclose the reliability of measurement results, simulation results suggest that this does not translate to every sensor system due to unfavorable arrangements of baseline drifts paired with sensitivity drift.
Developing Sidewalk Inventory Data Using Street View Images
Authors: Kang Bumjoon , Lee Sangwon , Zou Shengyuan
Published: May 2021

(1) Background: Public sidewalk GIS data are essential for smart city development. We developed an automated street-level sidewalk detection method with image-processing Google Street View data. (2) Methods: Street view images were processed to produce graph-based segmentations. Image segment regions were manually labeled and a random forest classifier was established. We used multiple aggregation steps to determine street-level sidewalk presence. (3) Results: In total, 2438 GSV street images and 78,255 segmented image regions were examined. The image-level sidewalk classifier had an 87% accuracy rate. The street-level sidewalk classifier performed with nearly 95% accuracy in most streets in the study area. (4) Conclusions: Highly accurate street-level sidewalk GIS data can be successfully developed using street view images.
Special Issue: Feature Papers to Celebrate the Inaugural Issue of Standards
Authors: Glavič Peter
Published: May 2021

We are glad to present the inaugural issue of the Standards journal [...]
Energy Transition at Home: A Survey on the Data and Practices That Lead to a Change in Household Energy Behavior
Authors: Gaspari Jacopo , Antonini Ernesto , Marchi Lia , Vodola Vincenzo
Published: May 2021

Since energy transition depends significantly on reducing the built environment’s energy needs, many regulations and incentives have been implemented globally over the last three decades. Despite some positive results, many scholars suggest that households’ behavioral change could greatly accelerate progress. People’s levels of awareness and willingness to change, as well as the provision of feedback technologies, are important factors affecting the process. In spite of the extent of this body of literature, household consumption keeps rising. Our thesis is that the subject has been investigated without considering some important correlations among factors. Therefore, this study developed a survey to investigate actual consumers’ perspectives on the topic by combining people’s awareness of energy use, interaction with metering devices, and user motivation into a coherent framework. A testing session involving 500 people was held as a validation phase for a future large-scale launch of the questionnaire. The test yielded some early outcomes on how people become more interested in changing as they gain more knowledge and are offered suggestions. However, despite their supposedly advanced knowledge as educators and students, the sample’s level of awareness was low, suggesting that a more user-centered approach is needed for wide-scale progress.
Source Apportionment of Heavy Metal Pollution in Agricultural Soils around the Poyang Lake Region Using UNMIX Model
Authors: Li Yanhong , Kuang Huifen , Hu Chunhua , Ge Gang
Published: May 2021

Rapid urbanization and industrialization have caused the continuous discharge of heavy metals into the soils of China’s Poyang Lake region, where they pose a major threat to human health. Yet, the spatial characteristics of these heavy metals in farmland soils and their pollution sources in this region remain unclear. This study was conducted to document the pollution caused by heavy metals in the Poyang Lake region through sampling that consisted of the collection of 215 soil samples from agricultural fields. The UNMIX model provided identification of the sources causing heavy metal pollution and source contributions to soil pollution. ArcGIS was used to study the spatial distribution of the eleven heavy metals and to validate the apportionment of pollution sources provided by the UNMIX model. Soil concentrations of heavy metals were above the local background concentrations. The average content of eight heavy metals, including Cd, Mo, Zn, Cu, Sb, W, Pb, and Ni, was approximately 1–6 times greater than natural background levels (6.91, 2.0, 1.67, 1.53, 1.23, 1.38, 1.11, and 1.24, respectively), while the average content of V, Cr, and Co was lower than natural background levels. The average contents of Cr, Ni, Cu, Zn, Cd, and Pb were all lower than the screening levels for unacceptable risks in agricultural land soils. The percentage of Cd content exceeded the risk screening value in all sampling sites, up to 55%, indicating that agricultural soils may significantly be affected by cadmium contamination. Five pollution sources of heavy metals were identified: natural sources, copper mine tailings, agricultural activities, atmospheric depositions, and industrial activities. The contribution rates of the pollution sources were 7%, 13%, 20%, 29%, and 31%, respectively. The spatial pattern of heavy metals was closely aligned with the outputs of the UNMIX model. The foregoing supports the utility of the UNMIX model for the identification of pollution sources of heavy metals, apportionment study, and its implementation in agricultural soils in the Poyang Lake region.
Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index
Authors: Yu Xinyang , Her Younggu , Zhu Xicun , Lu Changhe , Li Xuefei
Published: May 2021

Development of a high-accuracy method to extract arable land using effective data sources is crucial to detect and monitor arable land dynamics, servicing land protection and sustainable development. In this study, a new arable land extraction index (ALEI) based on spectral analysis was proposed, examined by ground truth data, and then applied to the Hexi Corridor in northwest China. The arable land and its change patterns during 1990–2020 were extracted and identified using 40 Landsat TM/OLI images acquired in 1990, 2000, 2010, and 2020. The results demonstrated that the proposed method can distinguish arable land areas accurately, with the User’s (Producer’s) accuracy and overall accuracy (kappa coefficient) exceeding 0.90 (0.88) and 0.89 (0.87), respectively. The mean relative error calculated using field survey data obtained in 2012 and 2020 was 0.169 and 0.191, respectively, indicating the feasibility of the ALEI method in arable land extracting. The study found that arable land area in the Hexi Corridor was 13217.58 km2 in 2020, significantly increased by 25.33% compared to that in 1990. At 10-year intervals, the arable land experienced different change patterns. The study results indicate that ALEI index is a promising tool used to effectively extract arable land in the arid area.
Changes in the Soundscape of the Public Space Close to a Highway by a Noise Control Intervention
Authors: Van Renterghem Timothy , Aletta Francesco , Botteldooren Dick
Published: May 2021

The deployment of measures to mitigate sound during propagation outdoors is most often a compromise between the acoustic design, practical limitations, and visual preferences regarding the landscape. The current study of a raised berm next to a highway shows a number of common issues like the impact of the limited length of the noise shielding device, initially non-dominant sounds becoming noticeable, local drops in efficiency when the barrier is not fully continuous, and overall limited abatement efficiencies. Detailed assessments of both the objective and subjective effect of the intervention, both before and after the intervention was deployed, using the same methodology, showed that especially the more noise sensitive persons benefit from the noise abatement. Reducing the highest exposure levels did not result anymore in a different perception compared to more noise insensitive persons. People do react to spatial variation in exposure and abatement efficiency. Although level reductions might not be excessive in many real-life complex multi-source situations, they do improve the perception of the acoustic environment in the public space.
The Influence of R&D in Mining on Sustainable Development in China
Authors: Du Jianguo , Dabuo Francis Tang , Madzikanda Beverlley , Boamah Kofi Baah
Published: May 2021

Mining and the utilization of mineral resources, especially coal for energy consumption, are considered a major contributor to China’s total index of environmental pollution, but there is less focus on its sustainable development. This study focused on the influence of research and development (R&D) on the sustainable development capabilities of 45 coal mining cities in China from 2008 to 2017. These cities were grouped into growing, maturity, declining, and regeneration categories. A DEAP model together with the Malmquist productivity index were used in calculating their sustainable development capabilities. It emerged that the R&D inclination for the coal mining cities was low at an average of 0.3406 and its influence has not pushed enough to reach the production frontier. The overall sustainable development capabilities of the four categories of coal mining cities were 0.6918 and also proved to have an unstable trend. There was evidence of inefficiencies in some categories of resource input and output. Technological changes (TECHCH) that promote the sustainable development capabilities grew at 12.2% for the period, which is moderately significant but still needs improvement. Major factors hindering the sustainable development of coal mining cities were insufficient desired input indicators including decisional capabilities, recovery in the treatment of pollution, and effective utilization of resources.
Spatiotemporal Variations of Landscape Ecological Risks in a Resource-Based City under Transformation
Authors: Wang Dong , Ji Xiang , Li Cheng , Gong Yaxi
Published: May 2021

The development of traditional resource-based cities requires drastic changes owing to the exhaustion of resources. During this transformation, the ecological environment of resource-based cities is threatened because of resource exploitation, in addition to the ecological risks caused by urban expansion. However, there is currently a lack of research on the evolution of ecological dangers in cities during this transformational period. Therefore, conducting relevant studies is essential to establishing a mechanism to mitigate these dangers. The present study analyzed Xuzhou, a typical resource-based city in China, as a case study. The main objective was to consider the dynamic changes in land use and ecological risks during the transformation of this resource-based city. The land-use changes in Xuzhou in 2000, 2010, and 2020 were analyzed, using the Markov model and landscape-pattern indices, allowing an ecological risk-assessment model of land-use changes to be constructed. Additionally, the spatial heterogeneity of ecological risks was evaluated by using spatial autocorrelation. The results showed that urban expansion influenced land use in Xuzhou significantly. Owing to the rapid urban expansion, the area of extremely high-risk regions increased significantly in 2010. Furthermore, the subsidence areas caused by mining had profound impacts on the region’s ecology, and early interventions for ecological restoration are needed to prevent further deterioration. During the transformation, Xuzhou’s overall ecological risks reduced gradually, which was conducive to its transition into an ecological city.
COVID-19: An Outcome of Biodiversity Loss or a Conspiracy? Investigating the Attitudes of Environmental Students
Authors: Tsantopoulos Georgios , Papageorgiou Aristotelis C. , Karasmanaki Evangelia
Published: May 2021

The global environment is being constantly degraded, placing humans at increased risk for outbreaks of infectious diseases. In this regard, environmental quality must be enhanced in order to prevent pandemics in the future. However, it is unknown whether future environmental experts are aware of the intricate relationship between environmental degradation and infectious diseases. This question is important because if they lack awareness about this relationship, they may not be able to contribute to biodiversity conservation which, in turn, can prevent outbreaks of infectious diseases. Hence, the aim of this paper is to investigate the attitudes of environmental students towards the pandemic. The primary objective is to examine their views on the origin of COVID-19 and a secondary objective is to discover the factors that affect the endorsement of conspiracy and non-conspiracy theories on the origin of COVID-19. Our findings indicated that an alarmingly high percentage of students endorsed the conspiracy theory that COVID-19 is a man-made virus for which there was a vaccine before it emerged, whereas only one in five students perceived that the virus is associated with climate change. These students are the future scientists who will be responsible for biodiversity conservation and climate change mitigation. Therefore, it is necessary to pay more attention to environmental students, both in Greece and elsewhere, and examine if such perceptions stem from any deficiencies in curricula or from the effects of the media.
The Effectiveness of Online Education during Covid 19 Pandemic—A Comparative Analysis between the Perceptions of Academic Students and High School Students from Romania
Authors: Butnaru Gina Ionela , Niță Valentin , Anichiti Alexandru , Brînză Geanina
Published: May 2021

The COVID-19 pandemic has disrupted normal activities such as going to school, moving education online. Based on data gathered through a survey (N = 784), this paper analyses students’ perceptions regarding the effectiveness of online education in a period when this type of education is the only available option. Although several studies suggest that online education can be as effective as traditional education which requires attendance, few studies have focused on learner satisfaction with online instruction, particularly in the transition to online learning from traditional approaches. The results indicate that students react differently to online education, and their reaction is based on their proficiency in using online tools, their ability to technically access online courses, and the instructors’ manner in conducting learning activities.