bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficacy of Blackleg Major Resistance Genes in B. napus in Germany
Authors: Alnajar Dima , von Tiedemann Andreas , Koopmann Birger
Published: April 2022

Leptosphaeria maculans is one of the major pathogens of oilseed rape (B. napus). It causes blackleg disease, which accounts for significant yield losses worldwide. Using cultivars that harbor major resistance (R) genes is one of the most effective control methods. However, the efficacy of major R genes is related to the frequency of the corresponding avirulence (Avr) genes in a L. maculans population. In this paper, we report the Avr profiles of L. maculans populations and the ratio of its mating types in Northern and Central regions of Germany. Eleven Avr genes in five-hundred and seventy-four isolates were characterized either by applying cotyledon tests on a B. napus differential set or by amplifying avirulence gene-specific PCR markers. Fifty-two races were determined, among which the most dominant race was Avrlm6, -7, -11, AvrlepR1, -R2. Results showed that the resistance gene Rlm2 is 100% ineffective, some other major R genes such as Rlm1, Rlm3, Rlm4 and LepR3 are partially effective (with corresponding Avr frequencies ≤ 42%), while LepR1, LepR2, Rlm6, Rlm11 and Rlm7 can still provide relatively effective resistance in the German fields investigated (with corresponding Avr frequencies of 63–100%). Sexual reproduction is a factor that enhances the potential of L. maculans to evolve under selection pressure. Mating types of the L. maculans populations did not deviate from the ratio of 1:1 in the examined regions, indicating that sexual reproduction and ascospores play central roles in the L. maculans lifecycle. Overall, this study provides an important dataset for the establishment of a strategic plan to preserve the efficacies of major R genes in Germany by applying cultivar rotations of oilseed rape.
Mapping Molecular Networks within Clitoria ternatea Linn. against LPS-Induced Neuroinflammation in Microglial Cells, with Molecular Docking and In Vivo Toxicity Assessment in Zebrafish
Authors: Mat Zian Nurul Farah Adni , Swain Puspanjali , Mohd Faudzi Siti Munirah , Zakaria Norzalina , Wan Ibrahim Wan Norhamidah , Abu Bakar Noraini , Shaari Khozirah , Stanslas Johnson , Choi Tae-Ik , Kim Cheol-Hee
Published: April 2022

Clitoria ternatea Linn. (CT), or butterfly pea, is an Ayurvedic plant traditionally used as a brain tonic. Recently, it was reported to be of use in treating central nervous system (CNS) disorders, i.e., as an antistress treatment and antidepressant. In the present study, we report a detailed phytochemical profile of the ethyl acetate fraction of the flower of CT (CTF_EA) with significant neuroprotective and anti-neuroinflammatory properties in both LPS-activated BV-2 and SK-N-SH cells. Concurrently, the molecular network (MN) derived from the CTF_EA metabolome allows putative identification of flavonol 3-O-glycosides, hydrocinnamic acids, and primary metabolites. Molecular docking studies suggest that CTF_EA preferentially targets iNOS, resulting in a decrease in nitric oxide (NO). Furthermore, no toxic effects on normal embryonic development, blood vessel formation, and apoptosis are observed when CTF_EA is tested for in vivo toxicity in zebrafish models. The overall preliminary results suggest the anti-neuroinflammatory and neuroprotective effects of CT and provide scientific support for the efficacy of this medicinal plant at local and traditional levels. However, studies on the targeted isolation of bioactive metabolites, in-depth pharmacological efficacy, and safety in mammalian models are urgently needed to expand our understanding of this plant before it is developed into a promising therapeutic agent for brain-related diseases.
Application and Multi-Stage Optimization of Daylight Polymer 3D Printing of Personalized Medicine Products
Authors: Pyteraf Jolanta , Pacławski Adam , Jamróz Witold , Mendyk Aleksander , Paluch Marian , Jachowicz Renata
Published: April 2022

Additive technologies have undoubtedly become one of the most intensively developing manufacturing methods in recent years. Among the numerous applications, the interest in 3D printing also includes its application in pharmacy for production of small batches of personalized drugs. For this reason, we conducted multi-stage pre-formulation studies to optimize the process of manufacturing solid dosage forms by photopolymerization with visible light. Based on tests planned and executed according to the design of the experiment (DoE), we selected the optimal quantitative composition of photocurable resin made of PEG 400, PEGDA MW 575, water, and riboflavin, a non-toxic photoinitiator. In subsequent stages, we adjusted the printer set-up and process parameters. Moreover, we assessed the influence of the co-initiators ascorbic acid or triethanolamine on the resin’s polymerization process. Next, based on an optimized formulation, we printed and analyzed drug-loaded tablets containing mebeverine hydrochloride, characterized by a gradual release of active pharmaceutical ingredient (API), reaching 80% after 6 h. We proved the possibility of reusing the drug-loaded resin that was not hardened during printing and determined the linear correlation between the volume of the designed tablets and the amount of API, confirming the possibility of printing personalized modified-release tablets.
Striga hermonthica Suicidal Germination Activity of Potent Strigolactone Analogs: Evaluation from Laboratory Bioassays to Field Trials
Authors: Jamil Muhammad , Wang Jian You , Yonli Djibril , Ota Tsuyoshi , Berqdar Lamis , Traore Hamidou , Margueritte Ouedraogo , Zwanenburg Binne , Asami Tadao , Al-Babili Salim
Published: April 2022

The obligate hemiparasite Striga hermonthica is one of the major global biotic threats to agriculture in sub-Saharan Africa, causing severe yield losses of cereals. The germination of Striga seeds relies on host-released signaling molecules, mainly strigolactones (SLs). This dependency opens up the possibility of deploying SL analogs as “suicidal germination agents” to reduce the accumulated seed bank of Striga in infested soils. Although several synthetic SL analogs have been developed for this purpose, the utility of these compounds in realizing the suicidal germination strategy for combating Striga is still largely unknown. Here, we evaluated the efficacy of three potent SL analogs (MP3, MP16, and Nijmegen-1) under laboratory, greenhouse, and farmer’s field conditions. All investigated analogs showed around a 50% Striga germination rate, equivalent to a 50% reduction in infestation, which was comparable to the standard SL analog GR24. Importantly, MP16 had the maximum reduction of Striga emergence (97%) in the greenhouse experiment, while Nijmegen-1 appeared to be a promising candidate under field conditions, with a 43% and 60% reduction of Striga emergence in pearl millet and sorghum fields, respectively. These findings confirm that the selected SL analogs appear to make promising candidates as simple suicidal agents both under laboratory and real African field conditions, which may support us to improve suicidal germination technology to deplete the Striga seed bank in African agriculture.
The Influence of Low-Energy Impact Loads on the Properties of the Sandwich Composite with a Foam Core
Authors: Komorek Andrzej , Przybyłek Paweł , Szczepaniak Robert , Godzimirski Jan , Rośkowicz Marek , Imiłowski Szymon
Published: April 2022

Composite materials are widely used in the construction of means of transport. Due to their low density and high stiffness, sandwich composites generate significant interest. The authors conducted static and dynamic tests in order to determine the effect of density and core thickness on the mechanical properties of a sandwich composite. Particular attention was paid to the impact properties of such composites. Herex and Airex polymer foams of different densities were used as cores, whereas the faces were made up of two layers of fabrics: glass and carbon. The matrix base of the tested materials was made of epoxy resin cured with a dedicated hardener. As a result of the study, a significant influence of the core on the strength parameters of the tested spacer materials was found. The examined polymer foams were found to have different adhesive properties, which affected their residual strength after an impact and the nature of destruction of the studied composites. It was observed that sandwich composites with a thicker core of higher density have higher impact strength and resistance to puncture. In the sandwich composites, low-energy impact loads result in damage only to the layer to which the load has been applied and has a core, so repairing such an element is much easier than in classic layered composites without a core. What is very important is that, in contrast to classic laminates, the bottom cover of the composite is not destroyed at low-impact energy values.
Development of a Dual Drug-Loaded, Surfactant-Stabilized Contrast Agent Containing Oxygen
Authors: Patel Raj , Lacerda Quezia , Oeffinger Brian E. , Eisenbrey John R. , Rochani Ankit K. , Kaushal Gagan , Wessner Corinne E. , Wheatley Margaret A.
Published: April 2022

Co-delivery of cancer therapeutics improves efficacy and encourages synergy, but delivery faces challenges, including multidrug resistance and spatiotemporal distribution of therapeutics. To address these, we added paclitaxel to previously developed acoustically labile, oxygen-core, surfactant-stabilized microbubbles encapsulating lonidamine, with the aim of developing an agent containing both a therapeutic gas and two drugs acting in combination. Upon comparison of unloaded, single-loaded, and dual-loaded microbubbles, size (~1.7 µm) and yield (~2 × 109 microbubbles/mL) (~1.7) were not statistically different, nor were acoustic properties (maximum in vitro enhancements roughly 18 dB, in vitro enhancements roughly 18 dB). Both drugs encapsulated above required doses calculated for head and neck squamous cell carcinoma, the cancer of choice. Interestingly, paclitaxel encapsulation efficiency increased from 1.66% to 3.48% when lonidamine was included. During preparation, the combination of single drug-loaded micelles gave higher encapsulation (µg drug/g microbubbles) than micelles loaded with either drug alone (lonidamine, 104.85 ± 22.87 vs. 87.54 ± 16.41), paclitaxel (187.35 ± 8.38 vs. 136.51 ± 30.66). In vivo intravenous microbubbles produced prompt ultrasound enhancement within tumors lasting 3–5 min, indicating penetration into tumor vasculature. The ability to locally destroy the microbubble within the tumor vasculature was confirmed using a series of higher intensity ultrasound pulses. This ability to locally destroy microbubbles shows therapeutic promise that warrants further investigation.
Hydrometallurgical Recovery of Iron, Nickel, and Chromium from Stainless Steel Sludge with Emphasis on Solvent Extraction and Chemical Precipitation
Authors: Chen Wei-Sheng , Chen Yu-Chi , Lee Cheng-Han
Published: April 2022

Stainless steel has a variety of applications nowadays because of its mechanical strength and corrosion resistance. The large-scale machinery made up of stainless steel has an outstanding performance and endurance for manufacturing industries. However, stainless steel scraps accumulate with a lubricant to form sludge during the operation. To reduce the environmental hazards caused by sludge, this research attempts to construct a hydrometallurgical process to recover iron, nickel, and chromium from the sludge. The experiments could be divided into four parts. First, calcination was adopted to remove the oil and water content. The factors that have impacts on the leaching efficiency, such as the type of acid and the calcination temperature, were investigated in the second part. It was optimal that the sludge was calcined at 300 ℃ for 8 h and leached by 4 mol/L HCl. The results revealed that the leaching percentages of iron, nickel, and chromium were 97.6%, 98.1%, and 95.7%, respectively. In the two-stage solvent extraction procedure, Fe(III) could be efficiently recovered by using 0.1 mol/L bis(2-ethlhexyl) phosphate (D2EHPA) at pH 1.5 with an Aqueous/Organic ratio of 1 over 10 min. The results indicated that the extraction percentage of Fe(III) was beyond 99%. Eventually, the recoveries of nickel and chromium were respectively 99.5% and 75% through chemical precipitation.
The Governor, the Cow-Head, and the Thrashing Pillows: Negotiated “Restrictive Islam” in Early Twenty-First Century Southeast Asia?
Authors: Satha-Anand Chaiwat
Published: April 2022

There are obviously several ways to explore the issue of Islamic radicalism in Southeast Asia. Instead of focusing on explicit violence such as those carried out by jihadi groups or those associated with them, this research article chooses to examine three empirical cases of Muslims’ expression of “restrictive Islam” that have taken place in the public sphere in both majority and minority Muslim contexts of Southeast Asia. They are: Muslims’ calling for the removal of an elected Chinese Christian governor of Jakarta on account of blasphemy in Indonesia; Muslims’ cow head protest to intimidate Hindus in Malaysia; and some Muslims’ thrashing of pillows at a hospital for COVID-19 patients as an expression of vehement faith-based refusal and protest in Buddhist Thailand against health protocols issued by Thai officials in the current fight against the pandemic in Southern Thailand. This article argues that the “restrictive” lives that some Muslims lead in Southeast Asia today have to assume a negotiated form that is a mixture of “high artificiality”, recently adopted from a version of purist Islam they claim to be authentic, and the “pure normality” resulting from a combination of political reality informed by existing forms of governance in these countries and the legacy of how historical Islam arrived in this land. The result is that the “restrictive Islam” espoused by many Southeast Asian Muslims could not be overly “extreme” or “radical” but tends to appear in a somewhat “negotiated” form.
DRs-UNet: A Deep Semantic Segmentation Network for the Recognition of Active Landslides from InSAR Imagery in the Three Rivers Region of the Qinghai–Tibet Plateau
Authors: Chen Ximing , Yao Xin , Zhou Zhenkai , Liu Yang , Yao Chuangchuang , Ren Kaiyu
Published: April 2022

At present, Synthetic Aperture Radar Interferometry (InSAR) has been an important technique for active landslides recognition in the geological survey field. However, the traditional interpretation method through human–computer interaction highly relies on expert experience, which is time-consuming and subjective. To solve the problem, this study designed an end-to-end semantic segmentation network, called deep residual shrinkage U-Net (DRs-UNet), to automatically extract potential active landslides in InSAR imagery. The proposed model was inspired by the structure of U-Net and adopted a residual shrinkage building unit (RSBU) as the feature extraction block in its encoder part. The method of this study has three main advantages: (1) The RSBU in the encoder part incorporated with soft thresholding can reduce the influence of noise from InSAR images. (2) The residual connection of the RSBU makes the training of the network easier and accelerates the convergency process. (3) The feature fusion of the corresponding layers between the encoder and decoder effectively improves the classification accuracy. Two widely used networks, U-Net and SegNet, were trained under the same experiment environment to compare with the proposed method. The experiment results in the test set show that our method achieved the best performance; specifically, the F1 score is 1.48% and 4.1% higher than U-Net and SegNet, which indicates a better balance between precision and recall. Additionally, our method has the best IoU score of over 90%. Furthermore, we applied our network to a test area located in Zhongxinrong County along Jinsha River where landslides are highly evolved. The quantitative evaluation results prove that our method is effective for the automatic recognition of potential active landslide hazards from InSAR imagery.
Temporal and Spatial Changes in Evapotranspiration and Its Potential Driving Factors in Mongolia over the Past 20 Years
Authors: Ersi Cha , Bayaer Tubuxin , Bao Yuhai , Bao Yulong , Yong Mei , Zhang Xiang
Published: April 2022

Evapotranspiration (ET) plays an important role in the study of regional long-term water cycles. The water cycle in Mongolia has been seriously affected by global warming and the intensification of human activities. A significant relationship exists between climate factors and ET. In this paper, the temporal and spatial fluctuations and stability of ET in Mongolia from 2001 to 2020 were studied by using MOD16A2 ET, MOD13A2 NDVI and the climate data of ERA5-Land. ET trends were analysed by using the Breaks for Additive Season and Trend (BFAST) software package, Theil–Sen median trend analysis, Mann–Kendall method and Hurst index. The correlations between ET and temperature (Tem), precipitation (Pre), net solar radiation (Nsr), soil moisture (Swl) and human activities were determined by partial correlation analysis and a geographic detector. In the past 20 years, ET increased significantly in 49.4% of Mongolia, and NDVI also showed a significant increasing trend. BFAST detected two mutation years. ET decreased rapidly from 2006 to 2007 and increased rapidly from 2015 to 2016. In addition to winter, the meteorological factor that had a significant positive impact on ET in the east and west was Pre, whereas the impact of Tem was more obvious in central Mongolia. In winter, Tem had a great impact on ET. In the vegetation growing season, the joint action of NDVI and Pre greatly positively contributed to ET. The geographical detector showed that the influence of annual human factors on ET was weakened by changes in NDVI and Pre. In the growing season, Tem and Nsr increased nonlinearly to ET, and other natural and human factors showed bivariate enhancement. These results will help to understand the responses of ET changes to natural factors and human activities in Mongolia and provide data support for future research on ET and the water cycle.
Plant Ontogeny Strongly Influences SO2 Stress Resistance in Landscape Tree Species Leaf Functional Traits
Authors: Han Aru , Bao Yongbin , Liu Xingpeng , Tong Zhijun , Qing Song , Bao Yuhai , Zhang Jiquan
Published: April 2022

Sulfur dioxide (SO2) is a major atmospheric pollutant and abiotic stressor. Although physiological studies on abiotic stressors have focused on fully expanded leaves, the resistance of leaf functional traits to SO2 during individual leaf development has not been studied. Thus, this study aimed to conduct SO2 static artificial fumigation experiments to evaluate changes in leaf functional traits and resistance to SO2 for three common landscape tree species (Syringa oblata Lindl. (S. oblata), Prunus cerasifera var. atropurpurea Jack. (P. cerasifera), and Ulmus pumila ‘Jinye’ (U. pumila)) in Changchun City and ontogeny under SO2 stress. Samples were collected on three days in autumn (1 September, 9 September, and 19 September 2019) for two different leaf stages (10 days and 40 days). In addition, remote sensing data were combined to explore the resistance mechanisms of broadleaf forests to different SO2 concentration classes during different seasons on a large scale. The results showed that the chlorophyll content, leaf temperature, green-peak reflectance, and Fv/Fm (maximal photochemical efficiency) at 10 days were significantly lower than that at 40 days, regardless of sampling date or SO2 concentration. Additionally, in general the SO2 resistance for 10 days leaves was consistently smaller than those for 40 days leaves in 3 tree species. On 9 September, 10 days leaves of the three tree species showed different leaf resistance performances under different SO2 concentrations in the order: P. cerasifera > S. oblata > U. pumila. Lastly, the extent of resistance decreased with increasing ρ(SO2) classes in different seasons, and the SO2 resistance was affected by season. We conclude that mature leaves are more resistant to SO2 stress than young leaves are. These results will provide scientific guidance on artificial plant community construction and prevention of future vegetation degradation.
Semi-Supervised Learning for Defect Segmentation with Autoencoder Auxiliary Module
Authors: Sae-ang Bee-ing , Kumwilaisak Wuttipong , Kaewtrakulpong Pakorn
Published: April 2022

In general, one may have access to a handful of labeled normal and defect datasets. Most unlabeled datasets contain normal samples because the defect samples occurred rarely. Thus, the majority of approaches for anomaly detection are formed as unsupervised problems. Most of the previous methods have typically chosen an autoencoder to extract the common characteristics of the unlabeled dataset, assumed as normal characteristics, and determine the unsuccessfully reconstructed area as the defect area in an image. However, we could waste the ground truth data if we leave them unused. In addition, a suitable choice of threshold value is needed for anomaly segmentation. In our study, we propose a semi-supervised setting to make use of both unlabeled and labeled samples and the network is trained to segment out defect regions automatically. We first train an autoencoder network to reconstruct defect-free images from an unlabeled dataset, mostly containing normal samples. Then, a difference map between the input and the reconstructed image is calculated and feeds along with the corresponding input image into the subsequent segmentation module. We share the ground truth for both kinds of input and train the network with binary cross-entropy loss. Additional difference images can also increase stability during training. Finally, we show extensive experimental results to prove that, with help from a handful of ground-truth segmentation maps, the result is improved overall by 3.83%.
3D Kinect Camera Scheme with Time-Series Deep-Learning Algorithms for Classification and Prediction of Lung Tumor Motility
Authors: Puangragsa Utumporn , Setakornnukul Jiraporn , Dankulchai Pittaya , Phasukkit Pattarapong
Published: April 2022

This paper proposes a time-series deep-learning 3D Kinect camera scheme to classify the respiratory phases with a lung tumor and predict the lung tumor displacement. Specifically, the proposed scheme is driven by two time-series deep-learning algorithmic models: the respiratory-phase classification model and the regression-based prediction model. To assess the performance of the proposed scheme, the classification and prediction models were tested with four categories of datasets: patient-based datasets with regular and irregular breathing patterns; and pseudopatient-based datasets with regular and irregular breathing patterns. In this study, ‘pseudopatients’ refer to a dynamic thorax phantom with a lung tumor programmed with varying breathing patterns and breaths per minute. The total accuracy of the respiratory-phase classification model was 100%, 100%, 100%, and 92.44% for the four dataset categories, with a corresponding mean squared error (MSE), mean absolute error (MAE), and coefficient of determination (R2) of 1.2–1.6%, 0.65–0.8%, and 0.97–0.98, respectively. The results demonstrate that the time-series deep-learning classification and regression-based prediction models can classify the respiratory phases and predict the lung tumor displacement with high accuracy. Essentially, the novelty of this research lies in the use of a low-cost 3D Kinect camera with time-series deep-learning algorithms in the medical field to efficiently classify the respiratory phase and predict the lung tumor displacement.
Selection of Filtering and Image Texture Analysis in the Radiographic Images Processing of Horses’ Incisor Teeth Affected by the EOTRH Syndrome
Authors: Górski Kamil , Borowska Marta , Stefanik Elżbieta , Polkowska Izabela , Turek Bernard , Bereznowski Andrzej , Domino Małgorzata
Published: April 2022

Equine odontoclastic tooth resorption and hypercementosis (EOTRH) is one of the horses’ dental diseases, mainly affecting the incisor teeth. An increase in the incidence of aged horses and a painful progressive course of the disease create the need for improved early diagnosis. Besides clinical findings, EOTRH recognition is based on the typical radiographic findings, including levels of dental resorption and hypercementosis. This study aimed to introduce digital processing methods to equine dental radiographic images and identify texture features changing with disease progression. The radiographs of maxillary incisor teeth from 80 horses were obtained. Each incisor was annotated by separate masks and clinically classified as 0, 1, 2, or 3 EOTRH degrees. Images were filtered by Mean, Median, Normalize, Bilateral, Binomial, CurvatureFlow, LaplacianSharpening, DiscreteGaussian, and SmoothingRecursiveGaussian filters independently, and 93 features of image texture were extracted using First Order Statistics (FOS), Gray Level Co-occurrence Matrix (GLCM), Neighbouring Gray Tone Difference Matrix (NGTDM), Gray Level Dependence Matrix (GLDM), Gray Level Run Length Matrix (GLRLM), and Gray Level Size Zone Matrix (GLSZM) approaches. The most informative processing was selected. GLCM and GLRLM return the most favorable features for the quantitative evaluation of radiographic signs of the EOTRH syndrome, which may be supported by filtering by filters improving the edge delimitation.
AGs-Unet: Building Extraction Model for High Resolution Remote Sensing Images Based on Attention Gates U Network
Authors: Yu Mingyang , Chen Xiaoxian , Zhang Wenzhuo , Liu Yaohui
Published: April 2022

Building contour extraction from high-resolution remote sensing images is a basic task for the reasonable planning of regional construction. Recently, building segmentation methods based on the U-Net network have become popular as they largely improve the segmentation accuracy by applying ‘skip connection’ to combine high-level and low-level feature information more effectively. Meanwhile, researchers have demonstrated that introducing an attention mechanism into U-Net can enhance local feature expression and improve the performance of building extraction in remote sensing images. In this paper, we intend to explore the effectiveness of the primeval attention gate module and propose the novel Attention Gate Module (AG) based on adjusting the position of ‘Resampler’ in an attention gate to Sigmoid function for a building extraction task, and a novel Attention Gates U network (AGs-Unet) is further proposed based on AG, which can automatically learn different forms of building structures in high-resolution remote sensing images and realize efficient extraction of building contour. AGs-Unet integrates attention gates with a single U-Net network, in which a series of attention gate modules are added into the ‘skip connection’ for suppressing the irrelevant and noisy feature responses in the input image to highlight the dominant features of the buildings in the image. AGs-Unet improves the feature selection of the attention map to enhance the ability of feature learning, as well as paying attention to the feature information of small-scale buildings. We conducted the experiments on the WHU building dataset and the INRIA Aerial Image Labeling dataset, in which the proposed AGs-Unet model is compared with several classic models (such as FCN8s, SegNet, U-Net, and DANet) and two state-of-the-art models (such as PISANet, and ARC-Net). The extraction accuracy of each model is evaluated by using three evaluation indexes, namely, overall accuracy, precision, and intersection over union. Experimental results show that the proposed AGs-Unet model can improve the quality of building extraction from high-resolution remote sensing images effectively in terms of prediction performance and result accuracy.
Efficient Hardware Design and Implementation of the Voting Scheme-Based Convolution
Authors: Pereira Pedro , Silva João , Silva António , Fernandes Duarte , Machado Rui
Published: April 2022

Due to a point cloud’s sparse nature, a sparse convolution block design is necessary to deal with its particularities. Mechanisms adopted in computer vision have recently explored the advantages of data processing in more energy-efficient hardware, such as the FPGA, as a response to the need to run these algorithms on resource-constrained edge devices. However, implementing it in hardware has not been properly explored, resulting in a small number of studies aimed at analyzing the potential of sparse convolutions and their efficiency on resource-constrained hardware platforms. This article presents the design of a customizable hardware block for the voting convolution. We carried out an in-depth analysis to determine under which conditions the use of the voting scheme is justified instead of dense convolutions. The proposed hardware design achieves an energy consumption about 8.7 times lower than similar works in the literature by ignoring unnecessary arithmetic operations with null weights and leveraging data dependency. Access to data memory was also reduced to the minimum necessary, leading to improvements of around 55% in processing time. To evaluate both the performance and applicability of the proposed solution, the voting convolution was integrated into the well-known PointPillars model, where it achieves improvements between 23.05% and 80.44% without a significant effect on detection performance.
Automatic Muscle Artifacts Identification and Removal from Single-Channel EEG Using Wavelet Transform with Meta-Heuristically Optimized Non-Local Means Filter
Authors: Phadikar Souvik , Sinha Nidul , Ghosh Rajdeep , Ghaderpour Ebrahim
Published: April 2022

Electroencephalogram (EEG) signals may get easily contaminated by muscle artifacts, which may lead to wrong interpretation in the brain–computer interface (BCI) system as well as in various medical diagnoses. The main objective of this paper is to remove muscle artifacts without distorting the information contained in the EEG. A novel multi-stage EEG denoising method is proposed for the first time in which wavelet packet decomposition (WPD) is combined with a modified non-local means (NLM) algorithm. At first, the artifact EEG signal is identified through a pre-trained classifier. Next, the identified EEG signal is decomposed into wavelet coefficients and corrected through a modified NLM filter. Finally, the artifact-free EEG is reconstructed from corrected wavelet coefficients through inverse WPD. To optimize the filter parameters, two meta-heuristic algorithms are used in this paper for the first time. The proposed system is first validated on simulated EEG data and then tested on real EEG data. The proposed approach achieved average mutual information (MI) as 2.9684 ± 0.7045 on real EEG data. The result reveals that the proposed system outperforms recently developed denoising techniques with higher average MI, which indicates that the proposed approach is better in terms of quality of reconstruction and is fully automatic.
Heterogeneous Autonomous Robotic System in Viticulture and Mariculture: Vehicles Development and Systems Integration
Authors: Kapetanović Nadir , Goričanec Jurica , Vatavuk Ivo , Hrabar Ivan , Stuhne Dario , Vasiljević Goran , Kovačić Zdenko , Mišković Nikola , Antolović Nenad , Anić Marina , Kozina Bernard
Published: April 2022

There are activities in viticulture and mariculture that require extreme physical endurance from human workers, making them prime candidates for automation and robotization. This paper presents a novel, practical, heterogeneous, autonomous robotic system divided into two main parts, each dealing with respective scenarios in viticulture and mariculture. The robotic components and the subsystems that enable collaboration were developed as part of the ongoing HEKTOR project, and each specific scenario is presented. In viticulture, this includes vineyard surveillance, spraying and suckering with an all-terrain mobile manipulator (ATMM) and a lightweight autonomous aerial robot (LAAR) that can be used in very steep vineyards where other mechanization fails. In mariculture, scenarios include coordinated aerial and subsurface monitoring of fish net pens using the LAAR, an autonomous surface vehicle (ASV), and a remotely operated underwater vehicle (ROV). All robotic components communicate and coordinate their actions through the Robot Operating System (ROS). Field tests demonstrate the great capabilities of the HEKTOR system for the fully autonomous execution of very strenuous and hazardous work in viticulture and mariculture, while meeting the necessary conditions for the required quality and quantity of the work performed.
Are Translators Afraid of Artificial Intelligence?
Authors: Kirov Vassil , Malamin Bagryan
Published: April 2022

Artificial intelligence (AI) is a leading technology in the digital transformation. AI is expected to cause job losses in general, initially in professions associated with routine activities, and subsequently in the field of creative professions. The present article analysed the results of the authors’ own empirical sociological survey of the attitude of Bulgarian translators towards AI, and the ways in which it will change their profession. Most of them perceive artificial intelligence and automatization as threats to the profession. According to them, digital technologies and AI will modify the profession by relieving human translators of the routine, technical part of the job. Hence, translators will predominantly edit machine-translated texts, and teach artificial intelligence to perform machine translation. The conclusion of the analysis demonstrates that, in the case of Bulgarian translators, such pessimistic scenarios about mass jobs destruction are not justified. In addition, expectations of a deterioration in quality of work as a result of digitalization in the near future are not justified in the case of the translating profession. The present survey results serve as a basis for further research about the impact of artificial intelligence on other creative professions.
Religiosity, Religious Fundamentalism, Heterosexism, and Support for Lesbian and Gay Civil Rights: A Moderated Mediation Approach
Authors: Henry Richard S. , Perrin Paul B. , Smith Erin R.
Published: April 2022

Support for lesbian and gay (LG) civil rights has increased in recent decades, but heterosexism is still prevalent, particularly among highly religious populations. Evidence suggests, however, that it may not be affiliation, but rather conviction in one’s beliefs that relates to prejudicial attitudes. The aims of this study were to examine the relationships among religiosity, heterosexism, and level of support for LG civil rights, as well as potential moderating effects by religious fundamentalism. This study used Amazon’s Mechanical Turk (Mturk) to recruit a U.S. national sample (n = 407) to participate in an online survey. A mediation model was constructed with religiosity leading to heterosexism, which diminished support for LG civil rights. This mediation model was expanded into moderated mediations with three types of religious fundamentalism as moderators. Heterosexism fully mediated the relationship between religiosity and support for LG civil rights. A moderated mediation was observed for aspects of religious fundamentalism reflecting external authority and worldly rejection (but not fixed religion) such that the mediation was present only when participants had high levels of these types of religious fundamentalism. Despite the belief that religious people endorse higher levels of heterosexism and that this influences their support for LG civil rights, this is only true when religiosity is also coupled with fundamentalist belief systems reflecting external authority and worldly rejection.
Initial Validation of the Ambivalent Sexism Inventory in a Military Setting
Authors: Trut Vesna , Sinovčić Petra , Milavić Boris
Published: April 2022

The military is a work environment in which the underrepresentation of women and the presence of gender prejudices continue to exist. The present study validated the Ambivalent Sexism Inventory (ASI) for the Croatian military population. To determine the ASI scale’s basic metric characteristics, data were collected from a sample of 895 active-duty military personnel (445 men and 450 women). The study results determined satisfactory measurement characteristics for the ASI scale and confirmed the ambivalent sexism construct with its basic dimensions. Sexism in the military environment was found to a moderately high degree, and gender differences were observed. Three types of sexism endorsement were identified in both subsamples (egalitarian, moderate egalitarian and traditional for women, and moderate egalitarian, traditional and hostile for men), with additional differences detected in their socio–demographic and professional characteristics. The findings support the apparent exposure of women to sexism in the military environment, and suggest the need to raise awareness of the negative impact of gender prejudice on gender relations in the military.
Digitalization, Participation and Interaction: Towards More Inclusive Tools in Urban Design—A Literature Review
Authors: De Siqueira Gustavo , Malaj Sadmira , Hamdani Mayssa
Published: April 2022

The 11th sustainable development goal highlights the importance of making our cities more inclusive. For that, planning processes should become more engaging and empower citizens to actively participate in designing their environments. However, the COVID-19 crisis exposed inequalities and posed challenges to communal activities due to restrictions on face-to-face activities. These constraints brought many researchers and practitioners to rethink the process of co-designing workshops, putting digitalization in the spotlight. The present study consists of a systematic literature review focusing on understanding how digital technologies affect participatory approaches in urban design and how they have evolved since the 1990s. Also, it investigates the correlation between levels of participation and interaction in different types of collaborative design workshops held in communities. We found that many authors have been developing new methodologies and digital tools aiming to digitalize the co-designing experience through mediation. However, there is no evolutionary evidence of tools in the field creating bridges between digitalization, participation, and interaction. We argue that a research agenda is required to produce more sophisticated tools to tackle social barriers and support inclusive design towards sustainable urban development patterns.
Sustainable but Not Spontaneous: Co-Operatives and the Solidarity Funds in Italy
Authors: Bernardi Andrea , Berranger Cécile , Mannella Anita , Monni Salvatore , Realini Alessio
Published: April 2022

This paper aims to highlight the role of solidarity funds in the development and support of national co-operative movements. Those are financial institutions specialized in supporting the start-up and growth of co-operatives. By adopting a case study approach, our analysis shows that solidarity funds emerged globally with similar objectives. Our international comparison focuses on Italy but includes France, the United Kingdom and Québec as a specific Canadian province with a French institutional environment. Despite their crucial importance, there is limited available research on this subject. To this end, our paper has policy implications; we need to consider establishing such institutions in countries where co-operatives are lagging behind as traditional financial institutions are often unable to finance co-operatives because of their property rights regime.
Landscape Architecture Design and Well-Being—Research Challenges and Opportunities
Authors: Nordh Helena , Evensen Katinka H.
Published: April 2022

For this Special Issue (SI), we set out to gather empirical studies that examine relationships between the design of public urban outdoor environments and the well-being of users of these spaces [...]
Analysis of the Energy Efficiency of Le Corbusier’s Dwellings: The Cité Frugès, an Opportunity to Reuse Garden Cities Designed for Healthy and Working Life
Authors: González-Avilés Ángel Benigno , Pérez-Carramiñana Carlos , Galiano-Garrigós Antonio , Ibarra-Coves Fernando , Lozano-Romero Claudia
Published: April 2022

This paper looks at the energy efficiency of the Cité Frugès in Pessac, designed in 1924 by Le Corbusier. Many of the innovations introduced by the Modern movement, such as flat roofs, large windows and solar protection elements, are still evident in the way architecture is carried out today. Most of these contributions were implemented in the Cité Frugès. The aim is to evaluate the architectural design criteria that most influenced the energy performance of Le Corbusier’s works, and to analyse the improvement that could be achieved by energy rehabilitation. The methodology used consisted of a systematised study of the five dwellings designed by Le Corbusier. For the modelling and calculation of their energy performance the “Líder–Calener unified tool” was used for evaluation, under the standards of compliance with European regulations for nearly zero energy consumption buildings. Energy parameters, such as thermal transmittance, solar gains and overall annual energy demand, were tested. The results obtained provide information on energy performance and allow for the analysis of possible energy refurbishment alternatives. The analysis of the results makes it possible to identify and qualitatively and quantitatively assess the limitations of the most relevant architectural and construction aspects in relation to energy efficiency and to draw up an energy map of the Cité Frugès in Pessac.
Spatiotemporal Distribution of Drought and Humidity in China Based on the Pedj Drought Index (PDI)
Authors: Wu Xu , Shen Xiaojing , Li Jianshe
Published: April 2022

Drought is one of the most devastating natural disasters, especially in China. In drought assessment, the PDI has high robustness, is easier to obtain than indices such as SPEI and PDSI, and is more advantageous in regions with sparse stations. The present study employs the annual PDI with the precipitation and temperature data from 830 meteorological stations to systematically study the interannual variation characteristics of drought and humidity in China during 1970–2019. The results showed the following: (1) 26.6% of the total statistics from meteorological stations showed significant (p < 0.05) increases in annual PDI values throughout China during 1970–2019. (2) Air temperature plays a more remarkable role than precipitation in assessing the drying trend with PDI throughout China. (3) About 71% of stations experienced more drought events (PDI > 1) than humidity events (PDI < −1), 14% of stations experienced more humidity events than drought events. (5) All stations experienced drought events (PDI > 1) with a frequency range from 6% to 32% and humidity events (PDI < −1) with a frequency range from 8% to 36%. Most of the stations experienced extreme drought events (PDI > 3) with a frequency range from 2% to 10%, while only 177 stations experienced extreme humidity events (PDI < −3) with a frequency range from 2% to 4%. (6) More than 67% of stations experienced drought conditions during both periods of 1972–1974 and 2000–2002 and even exceeded 80% in the three years 1972, 2000, and 2001. Both periods of 1976–1983 and 1985–1999 can be considered to be a humidity period throughout China. In conclusion, the PDI successfully expresses the interannual variation characteristics of drought and humidity events throughout China previously captured by other prominent, recommended drought indices.
‘Sustainable’ Recording and Preservation of Zangniang Stupa and Sangzhou Lamasery in Qinghai, China with Heritage Building Information Model
Authors: Xu Chaoran , Zhao Yi , Wu Cong
Published: April 2022

This paper research and discusses the ‘sustainable’ workflow and heritage recording method of historic building information modelling (HBIM) for Chinese Tibetan architecture and pagodas and explains the vital role of recording heritage information to protect cultural relics. Considering the Tibetan Buddhist Pagoda in Yushu, Qinghai, China, this paper explores the collaborative modelling mechanism and ideas between heritage surveying and scanning information and software, and the problems of these two methods. Through research, we have obtained successful cases of HBIM based on field scanning and mapping, online software collaborative modelling (Rhino, Bentley, Autodesk Computer-Aided Design), sustainable management, and display. It is an information model constructed according to construction logic and accurate information and one that realises sustainable and full-cycle recording functions by continuous recording, updating, and iterating. This method removes a limitation of HBIM in that it considers one-time information construction and delivery mode but does not consider and explore sustainable recording work. It will significantly promote more records on the heritage information of Tibetan architecture. The results will also directly serve the protection of architectural heritage in Qinghai Province, China and the ‘Silk Road (South Asia Section) Transnational Serial Application for World Heritage’ work.
Investigating a Retrofit Thermal Power Plant from a Sustainable Environment Perspective—A Fuel Lifecycle Assessment Case Study
Authors: Wu Yihsuan , Hua Jian
Published: April 2022

Retrofitting thermal power plants is a valuable opportunity to guide Taiwan’s electricity generation towards sustainability. Using an existing power plant nearing decommissioning as a case study, we hypothesized about fuel source options for retrofitting the power plant and compared the resulting impact on lifecycle atmospheric emissions. Our use of the lifecycle assessment (LCA) methodology reflected Taiwan’s heavy reliance on the imports and shipping of primary energy sources. We found that after accounting for the contribution of liquefaction and regasification (17%), gas-fired electricity still has significantly lower lifecycle greenhouse gases (GHGs) than coal or fuel oil (FO). In addition, we found that if natural gas (NG) is selected to achieve the greenhouse gas reduction of thermal power, the co-benefit of air pollution reduction can also be achieved at the same time.
Resilience of the Romanian Independent Cultural Sector under COVID-19 Pandemic Using the Grounded Theory
Authors: Marian-Potra Alexandra-Camelia , Pop Ana-Maria , Hognogi Gheorghe-Gavrilă , Nagy Júlia A.
Published: April 2022

In the event of any crisis, such as, in this case, the COVID-19 pandemic, new challenges arise, ranging from social and environmental phenomena to economic issues. One of the most affected economic sectors was the cultural one, especially independent artists, whose financial stability is usually inconsistent. The aim of this article was to test the immediate reactions of the cultural sector, both public and private, to the pandemic shock and, implicitly, to the restrictions imposed during the state of emergency in Romania (27 February–14 May 2020). By using grounded theory, 36 public documents of cultural stakeholders were coded and analyzed. All documents were identified in the Romanian online environment during the state of emergency. Based on the identified interrelationships, it was found that the independent contractors, self-employed workers in the creative-cultural sector, whether or not associated with NGOs or employees of public institutions, need financial and community support. However, the resilience of the cultural sector is conditioned by the creation of new multi-level policies for crisis management.