bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of a Novel Biosurfactant with Antimicrobial Activity Produced by Rhodococcus opacus R7
Authors: Zampolli Jessica , De Giani Alessandra , Di Canito Alessandra , Sello Guido , Di Gennaro Patrizia
Published: February 2022

Rhodococcus members excrete secondary metabolites, especially compounds which act as biosurfactants. In this work, we demonstrated the ability of Rhodococcus opacus R7 to produce a novel bioactive compound belonging to the class of biosurfactants with antimicrobial properties during the growth on naphthalene. Chemical and biochemical analyses of the isolated compound demonstrated that the biosurfactant could be classified as a hydrophobic peptide. The ESI-full mass spectrometry revealed that the isolated biosurfactant showed a molecular weight of 1292 Da and NMR spectra evidenced the composition of the following amino acid residues: Ala, Thr, Asp, Gly, Ser. Surfactant activity of the R. opacus R7 compound was quantified by the critical micelle dilution (CMD) method and the critical micelle concentration (CMC) was estimated around 20 mg L−1 with a corresponding surface tension of 48 mN m−1. Moreover, biological assays demonstrated that R. opacus R7 biosurfactant peptide exhibited antimicrobial activity against Escherichia coli ATCC 29522 and Staphylococcus aureus ATCC 6538 with the minimum inhibition growth concentration (MIC) values of 2.6 mg mL−1 and 1.7 mg mL−1, respectively. In this study for the first time, a hydrophobic peptide with both biosurfactant and antimicrobial activity was isolated from a bacterium belonging to Rhodococcus genus.
Special Issue: Microbial Impact on Cholesterol and Bile Acid Metabolism
Authors: Ridlon Jason M.
Published: February 2022

An important current focus in microbiome science is the biotransformation and degradation of cholesterol, steroids, and bile acids [...]
Emergence of Novel Chlamydia trachomatis Sequence Types among Chlamydia Patients in the Republic of Belarus
Authors: Feodorova Valentina A. , Saltykov Yury V. , Kolosova Anna A. , Rubanik Liudmila V. , Poleshchuk Nikolay N. , Motin Vladimir L.
Published: February 2022

Chlamydia trachomatis (CT) is a major cause of sexually transmitted diseases worldwide. The multilocus sequence typing (MLST) of clinical samples from random heterosexual chlamydia patients who were either asymptomatic or reported clinical manifestations of genital chlamydiosis (n = 63) in each of the seven major regions of the Republic of Belarus in 2017–2018 revealed 12 different CT sequence types (STs). We found seven known STs, ST4, ST6, ST9, ST13, ST38, ST95 and ST110, and five novel variants, namely ST271–ST275, which have not been detected elsewhere thus far. The ST4 variant was predominant (27/63, 42.9%) and detected in six out of seven regions. The two most common STs, ST9 and ST13, were regularly seen in four out of seven regions. In contrast, the remaining STs, ST6, ST38, ST95, ST110, and novel STs271-275, surfaced randomly in different parts of the country. The emergence of novel STs was registered in two regions, namely Minsk (ST271 and ST275) and Brest (ST271, ST272, ST273, and ST274). All the STs of detected CT strains were clustered into two Groups, I and III, which are characteristic of CT urogenital strains. No STs typical for Group II, specific to the LGV strains, were revealed. Our study contributes to better understanding the genetic diversity and molecular evolution of CT, one of the most important pathogens in public health worldwide.
Organic and Inorganic Amendments Shape Bacterial Indicator Communities That Can, In Turn, Promote Rice Yield
Authors: Qiu Chongwen , Bao Yuanyuan , Petropoulos Evangelos , Wang Yiming , Zhong Zhenfang , Jiang Yaozhi , Ye Xuhong , Lin Xiangui , Feng Youzhi
Published: February 2022

The dynamic patterns of the belowground microbial communities and their corresponding metabolic functions, when exposed to various environmental disturbances, are important for the understanding and development of sustainable agricultural systems. In this study, a two-year field experiment with soils subjected to: chemical fertilization (F), mushroom residues (MR), combined application of chemical fertilizers and mushroom residues (MRF), and no-fertilization (CK) was conducted to evaluate the effect of fertilization on the soil bacterial taxonomic and functional compositions as well as on the rice yield. The highest rice yield was obtained under MRF. Soil microbial properties (microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), urease, invertase, acid phosphatase, and soil dehydrogenase activities) reflected the rice yield better than soil chemical characteristics (soil organic matter (SOM), total N (TN), total K (TK), available P (AP), available K (AK), and pH). Although the dominant bacterial phyla were not significantly different among fertilizations, 10 bacterial indicator taxa that mainly belonged to Actinobacteria (Nocardioides, Marmoricola, Tetrasphaera, and unclassified Intrasporangiaceae) with functions of xenobiotic biodegradation and metabolism and amino acid and nucleotide metabolism were found to strongly respond to MRF. Random Forest (RF) modeling further revealed that these 10 bacterial indicator taxa act as drivers for soil dehydrogenase, acid phosphatase, pH, TK, and C/N cycling, which directly and/or indirectly determine the rice yield. Our study demonstrated the explicit links between bacterial indicator communities, community function, soil nutrient cycling, and crop yield under organic and inorganic amendments, and highlighted the advantages of the combined chemical and organic fertilization in agroecosystems.
Carotenoids and Their Biosynthesis in Fungi
Authors: Sandmann Gerhard
Published: February 2022

Carotenoids represent a class of pigmented terpenoids. They are distributed in all taxonomic groups of fungi. Most of the fungal carotenoids differ in their chemical structures to those from other organisms. The general function of carotenoids in heterotrophic organisms is protection as antioxidants against reactive oxygen species generated by photosensitized reactions. Furthermore, carotenoids are metabolized to apocarotenoids by oxidative cleavage. This review presents the current knowledge on fungal-specific carotenoids, their occurrence in different taxonomic groups, and their biosynthesis and conversion into trisporic acids. The outline of the different pathways was focused on the reactions and genes involved in not only the known pathways, but also suggested the possible mechanisms of reactions, which may occur in several non-characterized pathways in different fungi. Finally, efforts and strategies for genetic engineering to enhance or establish pathways for the production of various carotenoids in carotenogenic or non-carotenogenic yeasts were highlighted, addressing the most-advanced producers of each engineered yeast, which offered the highest biotechnological potentials as production systems.
Thermodynamic Solubility Profile of Temozolomide in Different Commonly Used Pharmaceutical Solvents
Authors: Ahad Abdul , Shakeel Faiyaz , Raish Mohammad , Ahmad Ajaz , Bin Jardan Yousef A. , Al-Jenoobi Fahad I. , Al-Mohizea Abdullah M.
Published: February 2022

The solubility parameters, and solution thermodynamics of temozolomide (TMZ) in 10 frequently used solvents were examined at five different temperatures. The maximum mole fraction solubility of TMZ was ascertained in dimethyl sulfoxide (1.35 × 10−2), followed by that in polyethylene glycol-400 (3.32 × 10−3) > Transcutol® (2.89 × 10−3) > ethylene glycol (1.64 × 10−3) > propylene glycol (1.47 × 10−3) > H2O (7.70 × 10−4) > ethyl acetate (5.44 × 10−4) > ethanol (1.80 × 10−4) > isopropyl alcohol (1.32 × 10−4) > 1-butanol (1.07 × 10−4) at 323.2 K. An analogous pattern was also observed for the other investigated temperatures. The quantitated TMZ solubility values were regressed using Apelblat and Van’t Hoff models and showed overall deviances of 0.96% and 1.33%, respectively. Apparent thermodynamic analysis indicated endothermic, spontaneous, and entropy-driven dissolution of TMZ in all solvents. TMZ solubility data may help to formulate dosage forms, recrystallize, purify, and extract/separate TMZ.
Image-Based Annotation of Chemogenomic Libraries for Phenotypic Screening
Authors: Tjaden Amelie , Chaikuad Apirat , Kowarz Eric , Marschalek Rolf , Knapp Stefan , Schröder Martin , Müller Susanne
Published: February 2022

Phenotypical screening is a widely used approach in drug discovery for the identification of small molecules with cellular activities. However, functional annotation of identified hits often poses a challenge. The development of small molecules with narrow or exclusive target selectivity such as chemical probes and chemogenomic (CG) libraries, greatly diminishes this challenge, but non-specific effects caused by compound toxicity or interference with basic cellular functions still pose a problem to associate phenotypic readouts with molecular targets. Hence, each compound should ideally be comprehensively characterized regarding its effects on general cell functions. Here, we report an optimized live-cell multiplexed assay that classifies cells based on nuclear morphology, presenting an excellent indicator for cellular responses such as early apoptosis and necrosis. This basic readout in combination with the detection of other general cell damaging activities of small molecules such as changes in cytoskeletal morphology, cell cycle and mitochondrial health provides a comprehensive time-dependent characterization of the effect of small molecules on cellular health in a single experiment. The developed high-content assay offers multi-dimensional comprehensive characterization that can be used to delineate generic effects regarding cell functions and cell viability, allowing an assessment of compound suitability for subsequent detailed phenotypic and mechanistic studies.
Production of Large-Ring Cyclodextrins by Amylomaltases
Authors: Krusong Kuakarun , Ismail Abbas , Wangpaiboon Karan , Pongsawasdi Piamsook
Published: February 2022

Amylomaltase is a well-known glucan transferase that can produce large ring cyclodextrins (LR-CDs) or so-called cycloamyloses via cyclization reaction. Amylomaltases have been found in several microorganisms and their optimum temperatures are generally around 60–70 °C for thermostable amylomaltases and 30–45 °C for the enzymes from mesophilic bacteria and plants. The optimum pHs for mesophilic amylomaltases are around pH 6.0–7.0, while the thermostable amylomaltases are generally active at more acidic conditions. Size of LR-CDs depends on the source of amylomaltases and the reaction conditions including pH, temperature, incubation time, and substrate. For example, in the case of amylomaltase from Corynebacterium glutamicum, LR-CD productions at alkaline pH or at a long incubation time favored products with a low degree of polymerization. In this review, we explore the synthesis of LR-CDs by amylomaltases, structural information of amylomaltases, as well as current applications of LR-CDs and amylomaltases.
Immunomodulatory Properties of Masticadienonic Acid and 3α-Hydroxy Masticadienoic Acid in Dendritic Cells
Authors: Piñón-Zárate Gabriela , Reyes-Riquelme Fernanda , Sánchez-Monroy Ma Beatriz , Velasco-Torrez Mónica , Martínez-Vázquez Mariano , Cárdenas-Monroy Christian Adrian , Hernandez-Téllez Beatriz , Jarquín-Yáñez Katia , Herrera-Enríquez Miguel Ángel , Castell-Rodríguez Andrés Eliú
Published: February 2022

Dendritic cells are antigen-presenting cells, which identify and process pathogens to subsequently activate specific T lymphocytes. To regulate the immune responses, DCs have to mature by the recognition of TLR ligands, TNFα or IFNγ. These ligands have been used as adjuvants to activate DCs in situ or in vitro, with toxic effects. It has been shown that some molecules affect the immune system, e.g., Masticadienonic acid (MDA) and 3α-hydroxy masticadienoic acid (3α-OH MDA) triterpenes naturally occurring in several medicinal plants, since they activate the nitric oxide synthase in macrophages and induce T lymphocyte proliferation. The DCs maturation induced by MDA or 3a-OH MDA was determined by incubating these cells with MDA or 3α-OH MDA, and their phenotype was afterwards analyzed. The results showed that only 3α-OH MDA was able to induce DCs maturation. When mice with melanoma were inoculated with DCs/3α-OH MDA, a decreased tumor growth rate was observed along with an extended cell death area within tumors compared to mice treated with DCs incubated with MDA. In conclusion, it is proposed that 3α-OH MDA may be an immunostimulant molecule. Conversely, it is proposed that MDA may be a molecule with anti-inflammatory properties.
Association between the Erythrocyte Membrane Fatty Acid Profile and Cognitive Function in the Overweight and Obese Population Aged from 45 to 75 Years Old
Authors: Shen Jingyi , Li Jinchen , Hua Yinan , Ding Bingjie , Zhou Cui , Yu Huiyan , Xiao Rong , Ma Weiwei
Published: February 2022

Dietary fatty acid intake is closely related to the cognitive function of the overweight and obese population. However, few studies have specified the correlation between exact fatty acids and cognitive functions in different body mass index (BMI) groups. We aimed to explain these relationships and reference guiding principles for the fatty acid intake of the overweight and obese population. Normal weight, overweight, and obese participants were recruited to receive a cognitive function assessment and dietary survey, dietary fatty acids intake was calculated, and the erythrocyte membrane fatty acid profile was tested by performing a gas chromatography analysis. The percentages of saturated fatty acids (SFAs) in the obese group were higher, while monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) were lower than in the normal weight and overweight groups. In the erythrocyte membrane, the increase of n-3 PUFAs was accompanied by cognitive decline in the overweight group, which could be a protective factor for cognitive function in the obese group. High n-6 PUFAs intake could exacerbate the cognitive decline in the obese population. Dietary fatty acid intake had different effects on the cognitive function of overweight and obese people, especially the protective effect of n-3 PUFAs; more precise dietary advice is needed to prevent cognitive impairment.
Neurotherapy of Yi-Gan-San, a Traditional Herbal Medicine, in an Alzheimer’s Disease Model of Drosophila melanogaster by Alleviating Aβ42 Expression
Authors: Su Ming-Tsan , Jheng Yong-Sin , Lu Chen-Wen , Wu Wen-Jhen , Yang Shieh-Yueh , Chuang Wu-Chang , Lee Ming-Chung , Wu Chung-Hsin
Published: February 2022

Alzheimer’s disease (AD), a main cause of dementia, is the most common neurodegenerative disease that is related to the abnormal accumulation of amyloid β (Aβ) proteins. Yi-Gan-San (YGS), a traditional herbal medicine, has been used for the management of neurodegenerative disorders and for the treatment of neurosis, insomnia and dementia. The aim of this study was to examine antioxidant capacity and cytotoxicity of YGS treatment by using 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays in vitro. We explored neuroprotective effects of YGS treatment in alleviating Aβ neurotoxicity of Drosophila melanogaster in vivo by comparing survival rate, climbing index, and Aβ expressions through retinal green fluorescent protein (GFP) expression, highly sensitive immunomagnetic reduction (IMR) and Western blotting assays. In the in vitro study, our results showed that scavenging activities of free radical and SH-SY5Y nerve cell viability were increased significantly (p < 0.01–0.05). In the in vivo study, Aβ42-expressing flies (Aβ42-GFP flies) and their WT flies (mCD8-GFP flies) were used as an animal model to examine the neurotherapeutic effects of YGS treatment. Our results showed that, in comparison with those Aβ42 flies under sham treatments, Aβ42 flies under YGS treatments showed a greater survival rate, better climbing speed, and lower Aβ42 aggregation in Drosophila brain tissue (p < 0.01). Our findings suggest that YGS should have a beneficial alternative therapy for AD and dementia via alleviating Aβ neurotoxicity in the brain tissue.
Vienna Rectifier-Based Control of a PMSG Wind Turbine Generator
Authors: Alili Aimad , Camara Mamadou Baïlo , Dakyo Brayima
Published: February 2022

Vienna converters have several advantages, including low construction costs, improved total harmonics, and considerable reliability. Generally, they are used in applications with a high switching frequency, particularly in telecommunications, and their use in power generation systems is recent but promising. They can be an interesting solution for medium and large wind power systems as they have the advantage of a high power density compared to traditional two-level converters. In this paper, a wind energy production system based on a Vienna rectifier and the permanent magnet synchronous generator (PMSG) is proposed. The main objective of this work is to evaluate the performance of the vector control strategy of the PMSG associated with the Vienna rectifier considering the real conditions of wind power systems. The feasibility and effectiveness of the proposed control strategy are evaluated through the simulations in MATLAB/Simulink and experimental tests based on a laboratory prototype. The outcomes present interesting performances in terms of dynamics and stability.
Genistein, a Potential Phytochemical against Breast Cancer Treatment-Insight into the Molecular Mechanisms
Authors: Sohel Md , Biswas Partha , Al Amin Md. , Hossain Md. Arju , Sultana Habiba , Dey Dipta , Aktar Suraiya , Setu Arifa , Khan Md. Sharif , Paul Priyanka , Islam Md. Nurul , Rahman Md. Ataur , Kim Bonglee , Al Mamun Abdullah
Published: February 2022

Breast cancer (BC) is one of the most common malignancies in women. Although widespread successful synthetic drugs are available, natural compounds can also be considered as significant anticancer agents for treating BC. Some natural compounds have similar effects as synthetic drugs with fewer side effects on normal cells. Therefore, we aimed to unravel and analyze several molecular mechanisms of genistein (GNT) against BC. GNT is a type of dietary phytoestrogen included in the flavonoid group with a similar structure to estrogen that might provide a strong alternative and complementary medicine to existing chemotherapeutic drugs. Previous research reported that GNT could target the estrogen receptor (ER) human epidermal growth factor receptor-2 (HER2) and several signaling molecules against multiple BC cell lines and sensitize cancer cell lines to this compound when used at an optimal inhibitory concentration. More specifically, GNT mediates the anticancer mechanism through apoptosis induction, arresting the cell cycle, inhibiting angiogenesis and metastasis, mammosphere formation, and targeting and suppressing tumor growth factors. Furthermore, it acts via upregulating tumor suppressor genes and downregulating oncogenes in vitro and animal model studies. In addition, this phytochemical synergistically reverses the resistance mechanism of standard chemotherapeutic drugs, increasing their efficacy against BC. Overall, in this review, we discuss several molecular interactions of GNT with numerous cellular targets in the BC model and show its anticancer activities alone and synergistically. We conclude that GNT can have favorable therapeutic advantages when standard drugs are not available in the pharma markets.
Identifying Graphite Purity by Weighted Fusion Method
Authors: Xu Xiaoping , Yu Xiangjia , Liu Guangjun , Wang Feng
Published: February 2022

The purity of graphite often affects its application in different fields. In view of the low efficiency of manual recognition and the omission of features extracted by single convolution neural network, this paper proposes a method for identifying graphite purity using a multi-model weighted fusion mechanism. The ideas suggested in this paper are as follows. On the self-built small sample data set, offline expansion and online enhancement are carried out to improve the generalization ability of the model and reduce the overfitting problem of deep convolution neural networks. Combined with transfer learning, a dual-channel convolution neural network is constructed using the optimized Alex Krizhevsky Net (AlexNet) and Alex Krizhevsky Net 50 (AlexNet50) to extract the deep features of the graphite image. After the weighted fusion of the two features, the Softmax classifier is used for classification. Experimental results show that recognition accuracy after weighted fusion is better than that of single network, reaching 97.94%. At the same time, the stability of the model is enhanced, and convergence speed is accelerated, which proves the feasibility and effectiveness of the proposed method.
Research on Predictive Control Algorithm of Vehicle Turning Path Based on Monocular Vision
Authors: Li Yufeng , Li Jingbin , Yao Qingwang , Zhou Wenhao , Nie Jing
Published: February 2022

To solve the issue that the monocular vision vehicle navigation system is limited by the field of vision acquired by the charge-coupled device camera and cannot acquire navigation turning path information throughout the turning process, decreasing the vehicle turning control accuracy, this paper proposed a turning control algorithm based on monocular vision vehicle turning path prediction. Firstly, the camera’s distortion was adjusted. Secondly, the camera imaging model was built, and the turning path’s position information was determined using the imaging position relationship. The vehicle motion model was built in accordance with the vehicle steering mode. Lastly, the cornering trajectory of a vehicle was estimated using the vehicle’s front axle length and front-wheel adjustment data, determining the vehicle turning point and turn operations on the basis of the projected relationship between the vehicle turning track and the turning path position. The experimental results showed that the proposed algorithm can effectively measure the position parameters of the cornering path and complete vehicle cornering control. The maximum absolute error of intercept and slope in turn path position parameters were 0.2525 m and 0.014 m, respectively. The cornering control accuracy was 0.093 m and 0.085 m, which met the vehicle navigation cornering control requirements. At the same time, the research can provide theoretical reference for research on precise navigation control of other cornering vehicles and other path guidance modes.
Electrochemical Performance of Al-1Zn-0.1In-0.1Sn-0.5Mg-xMn (x = 0, 0.1, 0.2, 0.3) Alloys Used as the Anode of an Al-Air Battery
Authors: Zhang Wenfeng , Hu Tongrui , Chen Tao , Yang Xiaowei , Zhu Yunfeng , Yang Tainian , Li Liquan
Published: February 2022

In this work, Al-1Zn-0.1In-0.1Sn-0.5Mg-xMn (x = 0, 0.1, 0.2, 0.3) alloys are prepared and used as the anode of an Al-air battery (AAB). We use scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS) and optical microscopy (OM) to analyze the microstructures of the alloys. The hydrogen evolution rate, electrochemical performance (including polarization curves), electrochemical impedance spectroscopy (EIS), and battery performance of the samples are examined in the 4 M NaOH electrolyte. The experimental data display that the average grain size is significantly refined after adding manganese into the Al-1Zn-0.1In-0.1Sn-0.5Mg alloy, with a decrease in grain size from over 100 μm to about 10 μm. The improved activity of the aluminum anode in the AAB can be attributed to the introduction of manganese. The Al-1Zn-0.1In-0.1Sn-0.5Mg-0.1Mn alloy possesses the optimal overall performance with a lower self-corrosion rate (0.128 mL∙cm−2∙min−1), the highest working potential (1.630 V) and energy density (2415 mWh·g−1), a higher capacity (1481 mAh·g−1) and anodic utilization (49.75%).
Intelligent Natural Gas and Hydrogen Pipeline Dispatching Using the Coupled Thermodynamics-Informed Neural Network and Compressor Boolean Neural Network
Authors: Zhang Tao , Bai Hua , Sun Shuyu
Published: February 2022

Natural gas pipelines have attracted increasing attention in the energy industry thanks to the current demand for green energy and the advantages of pipeline transportation. A novel deep learning method is proposed in this paper, using a coupled network structure incorporating the thermodynamics-informed neural network and the compressor Boolean neural network, to incorporate both functions of pipeline transportation safety check and energy supply predictions. The deep learning model is uniformed for the coupled network structure, and the prediction efficiency and accuracy are validated by a number of numerical tests simulating various engineering scenarios, including hydrogen gas pipelines. The trained model can provide dispatchers with suggestions about the number of phases existing during the transportation as an index showing safety, while the effects of operation temperature, pressure and compositional purity are investigated to suggest the optimized productions.
Effect of Partial Substitution of Sodium Chloride (NaCl) with Potassium Chloride (KCl) Coupled with High-Pressure Processing (HPP) on Physicochemical Properties and Volatile Compounds of Beef Sausage under Cold Storage at 4 °C
Authors: Ojangba Theodora , Zhang Li , Boamah Solomon , Gao Yanglei , Wang Zhuo , Amagloh Francis Kweku
Published: February 2022

This study aimed to evaluate the effects of partial substitution of sodium chloride (NaCl) with potassium chloride (KCl) in combination with high-pressure processing (HPP) on the physicochemical properties and volatile compounds of beef sausage during cold storage at 4 °C. Significant differences were found in the volatile compounds of beef sausages with 0%, 25%, and 50% NaCl contents partially substituted with KCl subjected to 28 days of storage and were well-visualized by heat map analysis. A total of 75 volatile compounds were identified and quantified in the beef sausages at the end of 28 days of storage, including 12 aldehydes, 4 phenols, 2 ketones, 18 alcohols, 8 acids, 3 esters, 14 terpenes, and 14 alkanes. Thirteen compounds had low odor activity values (OAV) (OAV < 1); however, high OAV (OAV > 1) were obtained after partial substitution of NaCl by KCl at 25% and 50% with HPP treatment compared to the non-HPP treated samples. In addition, 50% NaCl substitution with KCl in conjunction with HPP treatments increased thiobarbituric acid reactive substances (TBARS) by (0.46 ± 0.03 mg/MDA) compared with no HPP treatments. Replacement of 25% and 50% NaCl with KCl decreased TBARS by an average of 10.8% and 11.10%, respectively, compared to 100% NaCl coupled with HPP beef sausages. In summary, HPP and partial substitution of NaCl with KCl at 25% and 50% can be used to compensate for the reduction of NaCl in beef sausage by keeping the physical and flavor fraction at required levels.
Dialogicity in Individual and Institutional Scientific Blogs
Authors: Bondi Marina
Published: February 2022

The paper focuses on variation across institutional and individual scientific blogs, i.e., blogs that are managed by journals, magazines or associations involved in the dissemination of scientific information and blogs that are managed by individual researchers. Using comparable corpora of posts from different scientific disciplines, look in particular at markers of dialogicity, i.e., the representation of participants (markers of self-reference, reader-reference, as well as representation of the scientific community and markers of attribution), markers of communicative action (organizational units and metastatements), and evaluative dialogue (evaluative lexis and dialogic contraction or expansion). Concordance analysis of keywords and key-phrases (as calculated by Wordsmith Tools 8.0) shows that blogs managed by individual scientists emphasize personal voice and interpersonal elements, while institutional blogs are comparatively more informational. Dialogicity markers are shown to contribute to defining how bloggers manage subjective and intersubjective positioning and construct their credibility, thus defining the nature of their relation to the audience and ultimately the functions of blogging.
Evaluation of Vermicompost Produced by Using Post-Consumer Cotton Textile as Carbon Source
Authors: Singh Vijaypal , Wyatt Jordan , Zoungrana Ali , Yuan Qiuyan
Published: February 2022

A large amount of textile waste is generated every year around the globe. The textile product made from natural fibers might be vermicomposted and used as fertilizer. The present study aimed to research an integrated system of pre-composting (pathogen kill) and vermicomposting with various levels of post-consumer cotton waste to determine if this addition has any effects on the composting process. A vermicompost bin was constructed and filled with feedstocks mixed with post-consumer cotton textile waste at a 25:1 C:N ratio, and operated for three months at approximately 70% moisture content, with four composting trials with 0 g (control), 100 g, 200 g, and 300 g of textile waste. The pre-composting stage reached a temperature ranging from 40 °C to 50 °C, able to neutralize the pathogens. All four trials resulted in final compost with C: N ratios around 14, proving that post-consumer cotton textile waste did not affect the vermicomposting process, and was successfully used as a carbon source by worms to produce a healthy and mature compost. This indicates a sustainable option for the recovery of textile waste that is being decomposed in landfills.
An Integrated Platform for Ground-Motion Mapping, Local to Regional Scale; Examples from SE Europe
Authors: Poncoş Valentin , Stanciu Irina , Teleagă Delia , Maţenco Liviu , Bozsó István , Szakács Alexandru , Birtas Dan , Toma Ştefan-Adrian , Stănică Adrian , Rădulescu Vlad
Published: February 2022

Ground and infrastructure stability are important for our technologically based civilization. Infrastructure projects take into consideration the risk posed by ground displacement (e.g., seismicity, geological conditions and geomorphology). To address this risk, earth scientists and civil engineers employ a range of measurement technologies, such as optical/laser leveling, GNSS and, lately, SAR interferometry. Currently there is a rich source of measurement information provided in various formats that covers most of the industrialized world. Integration of this information becomes an issue that will only increase in importance in the future. This work describes a practical approach to address and validate integrated stability measurements through the development of a platform that could be easily used by a variety of groups, from geoscientists to civil engineers and also private citizens with no training in this field. The platform enables quick cross-validation between different data sources, easy detection of critical areas at all scales (from large-scale individual buildings to small-scale tectonics) and can be linked to end-users from various monitoring fields and countries for automated notifications. This work is closing the gap between the specialized monitoring work and the general public, delivering the full value of technology for societal benefits in a free and open manner. The platform is calibrated and validated by an application of SAR interferometry data to specific situations in the general area of the Romanian Carpathians and their foreland. The results demonstrate an interplay between anthropogenically induced changes and high-amplitude active tectono–sedimentary processes creating rapid regional and local topographic variations.
A Preliminary Numerical Study to Compare the Physical Method and Machine Learning Methods Applied to GPR Data for Underground Utility Network Characterization
Authors: Jaufer Rakeeb Mohamed , Ihamouten Amine , Goyat Yann , Todkar Shreedhar Savant , Guilbert David , Assaf Ali , Dérobert Xavier
Published: February 2022

In the field of geophysics and civil engineering applications, ground penetrating radar (GPR) technology has become one of the emerging non-destructive testing (NDT) methods thanks to its ability to perform tests without damaging structures. However, NDT applications, such as concrete rebar assessments, utility network surveys or the precise localization of embedded cylindrical pipes still remain challenging. The inversion of geometric parameters, such as depth and radius of embedded cylindrical pipes, as well as the dielectric parameters of its surrounding material, is of great importance for preventive measures and quality control. Furthermore, the precise localization is mandatory for critical underground utility networks, such as gas, power and water lines. In this context, innovative signal processing techniques associated with GPR are capable of performing physical and geometric characterization tasks. This paper evaluates the performance of a supervised machine learning and ray-based methods on GPR data. Support vector machines (SVM) classification, support vector machine regression (SVR) and ray-based methods are all used to correlate information about the radius and depth of embedded pipes with the velocity of stratified media in various numerical configurations. The approach is based on the hyperbola trace emerging in a set of B-scans, given that the shape of the hyperbola varies greatly with pipe depth and radius as well as with velocity of the medium. According to the ray-based method, an inversion of the wave velocity and pipe radius is performed by applying an appropriate nonlinear least mean squares inversion technique. Feature selection within machine learning models is also implemented on the information chosen from observed hyperbola travel times. Simulated data are obtained by means of the finite-difference time-domain (FDTD) method with the 2D numerical tool GprMax. The study is carried out on mono-static, ground-coupled GPR datasets. The preliminary study showed that the proposed machine learning methods outperforms the ray-based method for estimating radius, depth and velocity. SVR, for instance, calculates depth and radius values with mean absolute relative errors of 0.39% and 6.3%, respectively, with regard to the ground truth. A parametric comparison of the aforementioned methodologies is also included in the performance analysis in terms of relative error.
A Novel Physical Fatigue Assessment Method Utilizing Heart Rate Variability and Pulse Arrival Time towards Personalized Feedback with Wearable Sensors
Authors: Allik Ardo , Pilt Kristjan , Viigimäe Moonika , Fridolin Ivo , Jervan Gert
Published: February 2022

This paper proposes a novel method for physical fatigue assessment that can be applied in wearable systems, by utilizing a set of real-time measurable cardiovascular parameters. Daylength measurements, including a morning test set, physical exercise during the day, and an afternoon test set were conducted on 16 healthy subjects (8 female and 8 male). To analyze cardiovascular parameters for physical fatigue assessment, electrocardiography, pulse wave and blood pressure were measured during the test sets. The fatigue assessment questionnaire score, reaction time, countermovement jump height and hand grip strength were also measured and used as reference parameters. This study demonstrates that (i) the compiled test battery can selectively assess the rested vs. physically-fatigued states; (ii) the obtained linear support-vector machine, trained using the heart rate variability based parameter (F-score 0.842, accuracy 0.813) and pulse arrival time based parameter (F-score 0.875, accuracy 0.875) shows a promising ability to classify between the physically mildly fatigued and significantly fatigued states. Despite the somewhat limited study group size, the results of the study are unique and provide a significant advancement on the existing physical fatigue assessment methods towards a personalized and continuous real-time fatigue monitoring system with wearable sensors.
TraceBERT—A Feasibility Study on Reconstructing Spatial–Temporal Gaps from Incomplete Motion Trajectories via BERT Training Process on Discrete Location Sequences
Authors: Crivellari Alessandro , Resch Bernd , Shi Yuhui
Published: February 2022

Trajectory data represent an essential source of information on travel behaviors and human mobility patterns, assuming a central role in a wide range of services related to transportation planning, personalized recommendation strategies, and resource management plans. The main issue when dealing with trajectory recordings, however, is characterized by temporary losses in the data collection, causing possible spatial–temporal gaps and missing trajectory segments. This is especially critical in those use cases based on non-repetitive individual motion traces, when the user’s missing information cannot be directly reconstructed due to the absence of historical individual repetitive routes. Inserted in the context of location-based trajectory modeling, we tackle the problem by proposing a technical parallelism with the natural language processing domain. Specifically, we introduce the use of the Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art language representation model, into the trajectory processing research field. By training deep bidirectional representations from unlabeled location sequences, jointly conditioned on both left and right context, we derive an explicit predicted estimation of the missing locations along the trace. The proposed framework, named TraceBERT, was tested on a real-world large-scale trajectory dataset of short-term tourists, exploring an effective attempt of adapting advanced language modeling approaches into mobility-based applications and demonstrating a prominent potential on trajectory reconstruction over traditional statistical approaches.
A Dialectic of Race Discourses: The Presence/Absence of Mixed Race at the State, Institution, and Civil Society and Voluntary and Community Sector Levels in the United Kingdom
Authors: Njaka Chinelo L.
Published: February 2022

For the twenty years that mixed race has been on the United Kingdom (UK) censuses, the main story of mixed race in the UK remains one notable for its nominal presence and widespread absence in national discourses on race and ethnicity, racialisation, and racisms. The article explores reasons for this through connecting the continued presence/absence of mixed race in public discursive spheres to the role that White supremacy continues to play at systemic, structural, and institutional levels within UK society. As technologies of White supremacy, the article argues that continued marginalisation of mixed race has a direct connection to systemic, structural, and institutional aspects of race, racialisation, and racisms. Using three case studies, the article will use race-critical analyses to examine the ways that mixed race is present and—more often—absent at three societal levels: the state, institution, and civil society and voluntary and community sector. The paper will conclude by exploring key broad consequences for the persistent and common presence/absence of mixed race within race and racisms discourses as a technology of political power. Working in tandem, the paper exposes that presence/absence continues to affect mixed race people—and all racialised people—living in and under White supremacy.
Development of a Novel Nordic Hamstring Exercise Performance Test Device: A Reliability and Intervention Study
Authors: Augustsson Jesper , Augustsson Sofia Ryman
Published: February 2022

There is evidence that a knee flexor exercise, the Nordic hamstring exercise (NHE), prevents hamstring injuries. The purpose of this study was therefore to develop, and to determine the reliability of, a novel NHE test device and, further, to determine the effectiveness of a 10-week low volume NHE program on NHE performance. Twenty female football (soccer) players, aged 16–30 years, participated in this study. From a kneeling position on the device, with the ankles secured under a heavy lifting sling, participants leaned forward in a controlled manner as far as possible (eccentric phase) and then returned to the starting position (concentric phase). A tape measure documented the forward distance achieved by the participants in cm. Participants completed three separate occasions to evaluate test-retest reliability. Additionally, 14 players performed a low volume (1 set of 5 repetitions) NHE program once weekly for 10 weeks. No significant test-retest differences in NHE performance were observed. The intra-class correlation coefficient was 0.95 and the coefficient of variation was 3.54% between tests. Mean improvement in the NHE performance test by the players following training was 22% (8.7 cm), p = 0.005. Our test device reliably measured NHE performance and is easy to perform in any setting. Further, NHE performance was improved by a 10-week low volume NHE program. This suggests that even a small dose (1 set of 5 repetitions once weekly) of the NHE may enhance NHE performance.
Environmental Fate of Trace Elements in Depositional Sediments after Flashflood Events: The Case of Mandra Town in Greece
Authors: Kourgia Paraskevi Maria , Argyraki Ariadne , Paraskevopoulou Vasiliki , Botsou Fotini , Kelepertzis Efstratios , Dassenakis Manos
Published: February 2022

Flash floods are one of the harshest natural hazards, having a wide range of substantial impacts for human and environmental health in the short-term and long-term. On 15 November 2017, a high-intensity storm caused a catastrophic flash flood event in the town of Mandra, a western, outer suburb of the Athens Metropolitan Area in Greece. In this study, we determine the aqua regia extractable concentrations of trace elements in residual sediments and associated soils after the flash flood and evaluate the fractionation of contaminants in geochemical compartments. Geochemical data are coupled with physicochemical parameter measurements and mineralogy to identify possible factors explaining the variability of trace element concentrations, while a dilute acid extraction is used to monitor changes of the reactive fraction of the trace elements over the term of 1 year following the flood event. Aqua regia concentrations in flood-deposited sediments reached values of 1 mg/kg (Cd), 24 mg/kg (Co), 183 mg/kg (Cr), 599mg/kg (Cu), 1080 mg/kg (Mn), 195 mg/kg (Ni), 122 mg/kg (Pb) and 945 mg/kg (Zn). Multivariate statistical techniques classified the elements according to their natural or anthropogenic origin. Trace elements of geogenic origin (As, Co, Cr, Mn, Ni) dominate in flood deposited material. The cluster of anthropogenic elements (Cd, Cu, Pb, Zn,) shows significant correlation with total organic carbon and magnetic susceptibility, while a significant seasonal variation has been observed for total organic carbon, Cd and Mn contents in the deposited sediments. Results allow a better understanding of the distribution of elements in the surface cover during and after catastrophic events in urban areas and provide useful information on the long-term exposure of the residents.
Subsidized LPG Scheme and the Shift to Cleaner Household Energy Use: Evidence from a Tribal Community of Eastern India
Authors: Kalli Rajesh , Jena Pradyot Ranjan , Managi Shunsuke
Published: February 2022

Traditional fuels have both environmental and health impacts. The transition from traditional to clean cooking fuel requires significant public policy actions. The Pradhan Mantri Ujjwala Yojana (PMUY) is one of the primary policies launched in India to eradicate energy poverty among households. Past studies have focused on the drivers that motivate rural households to adopt clean energy and identified the bottlenecks for adoption of clean energy in developing countries. PMUY’s success in terms of scale and pace is critical in the national drive to provide access to clean energy fuel to each citizen. The present study focuses on two objectives. First, we investigate the intensity of adoption and refill of LPG under the PMUY scheme. Second, we use household and other demographic characteristics to examine the factors that influence households’ decision on using LPG as a cooking fuel. Empirical results show that rapid growth has been witnessed in the provision of subsidized LPG connections. However, the annual average refill status stands at two LPG cylinders per beneficiary household indicating that the majority of the beneficiaries have failed to refill their LPG cylinders. This imbalance between rapid enrollment of LPG and limited refill among beneficiary households indicate the continued usage of traditional sources of energy for cooking. From the primary survey conducted in the rural tribal communities of Odisha, we observe that household income and education played a significant role in adoption of LPG and continued usage of LPG gas. Additionally, the logit and ordered probit models identify that membership in self-help groups, accessibility and awareness of LPG are the major adoption drivers. In conclusion, policy makers need to address the challenge of refill status among PMUY consumers. Further, educating households on health benefits through SHG and creating accessibility at village level can actively increase the usage of LPG.
Review of the Impact of IT on the Environment and Solution with a Detailed Assessment of the Associated Gray Literature
Authors: Guillaume Bourgeois , Benjamin Duthil , Vincent Courboulay
Published: February 2022

The immaterial aspect of digital technology tends to make us forget its growing impact on the environment. Today, the situation has changed: we are becoming aware of the material aspect of digital technology, especially with the recent datacenter fires. The topic is now on the political agenda, and for good reason: digital accounts for nearly 4% of global emissions, and emissions from the sector are growing exponentially. Digital impact analysis is crucial to increase the visibility and consequently the diffusion and democratization of responsible digital. This article offers a detailed study and solutions on the environmental impact of IT with a detailed assessment of the gray literature of the last years and accompanying elements such as LCA or ISO standards. Thus, we have a view of the main green IT tools, the environmental impact of digital on datacenters, user equipment and networks, recent forecasts, and a look at the future challenges of digital technologies (such as AI or Blockchain),and finally a conclusion with the limitations of our research.
The Impacts of Energy Use, Tourism and Foreign Workers on CO2 Emissions in Malaysia
Authors: Rahman Arifur Rahman Atiqur , Shaari Mohd Shahidan , Masnan Faiz , Esquivias Miguel Angel
Published: February 2022

Previous studies have investigated various determinants of CO2 emissions, such as energy use, economic expansion and population growth. However, foreign workers have not been treated as a potential determinant. Therefore, this research embarks on an investigation into the impacts of energy use, foreign workers and tourist arrivals on CO2 emissions in Malaysia from 1982 to 2018. An ARDL approach was employed, and the findings showed that natural gas and electricity use insignificantly influence CO2 emissions. Tourist arrivals, coal use and oil use were found to positively influence CO2 emissions, while foreign workers and population growth insignificantly influence CO2 emissions. It was found that in the early stages of development, higher GDP negatively influences CO2 emissions, but in the final stages, higher GDP positively influences CO2 emissions. These findings are important for formulating policies to reduce environmental degradation stemming from higher CO2 emissions. Malaysia should use more renewable energy sources, and a carbon tax could be imposed to reduce environmental degradation.