bluuebunny/crossref_metadata_2025 huggingface dataset:
Innovative Coating–Etching Method of Biocarrier Fabrication for Treating Wastewater with a Low C/N Ratio
Authors: Yu Ning , Zhang Daijun , Lei Yu , Wang Jianhui , Dong Yang , Chen Youpeng
Published: July 2022

A novel method was used to fabricate the bio-carrier with both a high specific surface area and good compatibility. The results of monitoring the growth of biofilms at a low C/N ratio (0.83) showed that resulting carrier-PLA-cavity offered certain advantages for biofilm growth by providing an appropriate microenvironment for bacterial growth in wastewater treatment. The biofilm on carrier-PLA-cavity grew and updated faster than the naked-carrier. The biomass and thickness of biofilms growing on carrier-PLA-cavity were 10 kg/m3 and 500 μm, respectively. From the wastewater tests, 90% of the total nitrogen was removed via simultaneous nitrification and denitrification (SND) by the biofilm biomass attached to carrier-PLA-cavity, compared to 68% for the naked-carrier. The COD removal efficiency values of the carrier-PLA-cavity and naked-carrier were 94% and 86%, respectively. The microbial community analysis of carrier biofilms showed that Halomonas was the most abundant genus, and heterotrophic nitrification and denitrification were responsible for nitrogen removal in both reactors. Notably, this method does not require any complicated equipment or structural design. This novel method might be a promising strategy for fabricating biocarriers for treating wastewater with a low C/N ratio.
Effects of Mung Bean (Vigna radiata) Protein Isolate on Rheological, Textural, and Structural Properties of Native Corn Starch
Authors: Tarahi Mohammad , Hedayati Sara , Shahidi Fakhri
Published: July 2022

It is critical to understand the starch–protein interactions in food systems to obtain products with desired functional properties. This study aimed to investigate the influence of mung bean protein isolate (MBPI) on the rheological, textural, and structural properties of native corn starch (NCS) and their possible interactions during gelatinization. The dynamic rheological measurements showed a decrease in the storage modulus (G’) and loss modulus (G”) and an increase in the loss factor (tan δ), by adding MBPI to NCS gels. In addition, the textural properties represented a reduction in firmness after the addition of MBPI. The Scanning electron microscope (SEM) images of the freeze-dried NCS/MBPI gels confirmed that the NCS gel became softer by incorporating the MBPI. Moreover, X-ray diffraction (XRD) patterns showed a peak at 17.4°, and the relative crystallinity decreased with increasing MBPI concentrations. The turbidity determination after 120 h refrigerated storage showed that the addition of MBPI could reduce the retrogradation of NCS gels by interacting with leached amylose. Additionally, the syneresis of NCS/MBPI gels decreased at 14 days of refrigerated storage from 60.53 to 47.87%.
An In Vivo Pilot Study on Probiotic Potential of Lactic Acid Bacteria Isolated from the Gastrointestinal Tract of Creole Hens (Gallus gallus domesticus) Native to Montería, Córdoba, Colombia in Broiler Chickens
Authors: Betancur-Hurtado César A. , Barreto Lopez Luis Miguel , Rondon Castillo Ana Julia , Trujillo-Peralta Maria C. , Hernandez-Velasco Xochitl , Tellez-Isaias Guillermo , Graham Brittany D.
Published: July 2022

The objective of the present study was to characterize the probiotic potential of nine strains of Lactobacillus spp. isolated from the gastrointestinal tract of Creole hens through in vitro and in vivo tests. The following parameters were evaluated in vitro: (1) growth at four pH levels, (2) resistance to four bile salt concentrations, (3) tolerance to four NaCl concentrations, (4) growth capacity in the culture medium, and (5) the antimicrobial activity against Escherichia coli, Salmonella, Klebsiella, and Staphylococcus aureus. The candidate LP-40 had significantly (p < 0.05) increased resistance to pH 3 and 0.3% bile salts and elevated antimicrobial activity in vitro compared to the other strains evaluated. This strain was identified as Lactobacillus salivarius by 16S rRNA sequencing. An in vivo experiment was conducted to assess the effect of LP-40 supplementation in the drinking water on 42-day performance parameters in broiler chickens as compared to a non-treated control or dietary treatment with enrofloxacin. The administration of LP-40 in the drinking water significantly (p < 0.05) improved body weight, feed conversion compared to the antibiotic-treated control. Thus, the in vitro and in vivo results suggest that Lactobacillus salivarius LP-40 demonstrates probiotic potential and, perhaps, could be utilized as an alternative to antibiotic treatment.
The Trace Gas Monitoring Method Based on Diode Laser Wavelength-Modulation Spectroscopy Technology for the Detection of Clinical Blood Infection
Authors: Sun Jing , Song Yuxiao , Shi Dongxin , Wang Feifei , Yang Yong , Yao Pengyu , Song Binghong , Yu Yang , Jiang Chenyu , Cao Bingqiang
Published: July 2022

It is important to monitor and evaluate the growth of microorganisms in order to accurately judge the situation of blood microbial infection. In this paper, diode laser wavelength modulation spectroscopy (DLWMS) technology is used to design a set of low-cost, high sensitivity, fast dynamic responses and a non-invasive trace gas measurement system, which can quickly and accurately assess the concentration of carbon dioxide (CO2) produced by blood microbial reproduction. The measurement principle and spectral processing algorithm of DLWMS are introduced first. The automatic and rapid detection of CO2 is realized through a self-designed optical system. By using the system to detect blood infection, the accuracy of the technology was verified. Therefore, it also indicates that DLWMS CO2 monitoring is a highly sensitive, fast-response and non-invasive technology, which can accurately and quickly determine blood infection and meet the clinical application requirements of human septicemia, bacteremia and other diseases.
Doxological (Im)Purity? Nicholas of Cusa’s ‘Art of Praising’ and Liturgical Thinking in 21st Century
Authors: Bocken Inigo
Published: July 2022

It is noteworthy that the thinking of Nicholas of Cusa (1401–1464) has recurred again and again among prominent recent theologians who, critical of Modern rationality, have brought back to the fore the importance of liturgical praxis. Often, however, the mystical theology of Nicholas of Cusa had been presented during the Twentieth Century primarily as an unfinished precursor to Modern subject-philosophy in the line of Kant. In this contribution, I will consider this striking change of perspective against the background of recent debates concerning the role of liturgy not only for theology, but also for philosophy. Does Cusa’s ‘art of praising’ offer a way out of the dilemmas facing liturgical thought?
Local-Global Based High-Resolution Spatial-Spectral Representation Network for Pansharpening
Authors: Huang Wei , Ju Ming , Zhao Zhuobing , Wu Qinggang , Tian Erlin
Published: July 2022

Due to the inability of convolutional neural networks to effectively obtain long-range information, a transformer was recently introduced into the field of pansharpening to obtain global dependencies. However, a transformer does not pay enough attention to the information of channel dimensions. To solve this problem, a local-global-based high-resolution spatial-spectral representation network (LG-HSSRN) is proposed to fully fuse local and global spatial-spectral information at different scales. In this paper, a multi-scale feature fusion (MSFF) architecture is designed to obtain the scale information of remote sensing images. Meanwhile, in order to learn spatial texture information and spectral information effectively, a local-global feature extraction (LGFE) module is proposed to capture the local and global dependencies in the source images from a spatial-spectral perspective. In addition, a multi-scale contextual aggregation (MSCA) module is proposed to weave hierarchical information with high representational power. The results of three satellite datasets show that the proposed method exhibits superior performance in terms of both spatial and spectral preservation compared to other methods.
A Robust Dual-Platform GMTI Method against Nonuniform Clutter
Authors: Zou Mulan , Jin Guanghu , Li Liang , He Zhihua
Published: July 2022

The ground moving-target indication (GMTI) technique can detect civil and military moving targets, which means that this technique has received much attention. Strong clutter background suppression is one of the critical problems in this application. However, the detection performance in heterogeneous environment can be degraded due to the inaccurate estimation of the clutter covariance matrix (CCM). In this paper, we propose a robust GMTI method using a spaceborne dual-platform synthetic aperture radar (SAR) system, which can obtain highly accurate CCM in nonuniform clutter. Firstly, the accurate CCM is estimated based on the SAR image obtained by the former platform. Then, space–time adaptive processing (STAP) is carried out using the obtained the CCM. Finally, the detection threshold is set according to the estimated CCM and detection is executed accurately. Compared with the traditional CCM estimation method in STAP using the clutter nearby the cell under test, this method directly estimates the CCM using the clutter of the cell under test, which can avoid CCM estimation mistakes in heterogeneous clutter environment. The clutter can be whitened and depressed more effectively. Additionally, with the accurate threshold acquired from the CCM, the detection probability can be effectively improved under a certain false-alarm criterion. Based on simulation data, GMTI experiments in a heterogeneous environment such as clutter with strong pollution, junction zone of hot and cold clutter, and clutter with nonuniform power are carried out; the results show that the moving targets can be effectively detected with the proposed method.
Evaluation of BDS/GPS Multi-Frequency RTK Positioning Performance under Different Baseline Lengths
Authors: Wang Ershen , Song Wei , Zhang Yize , Shi Xiaozhu , Wang Zhi , Xu Song , Shu Wansen
Published: July 2022

The BeiDou Navigation Satellite System (BDS) is fully operational and provides positioning, navigation, and timing services to users worldwide. To comprehensively evaluate the BeiDou-3 Navigation Satellite System (BDS-3) global real-time kinematic (RTK) positioning performance, five sets of IGS/MEGX stations with different baseline lengths are selected in this research, and the visibility of current BDS-3, BDS-2+BDS-3, and Global Positioning System (GPS) system satellites are analyzed. The single frequency, dual-frequency, and triple-frequency positioning accuracy as well as ambiguity fixing rate under short baseline and long baseline are also analyzed. The experimental results show that the positioning accuracies of B1C, BII, L1, and B3I single-frequency bands were about the same, while for band B2a it was lower. For the short baseline dual-frequency RTK positioning mode, the accuracy of BDS-3 (B1C/B2a), BDS-3 (B1I/B3I), triple-frequency BDS-3 (B1C/B2a/B3I), and GPS (L1L2) is comparable and slightly better than that of BDS-3 (B1I/B3I). With the increase in baseline length, the advantages of dual-frequency BDS-3 (B1C/B2a) and triple frequency BDS (B1C/B2a/B3I) are more obvious, with triple-frequency BDS-3 (B1C/B2a/B3I) having the best positioning accuracy. In terms of ambiguity fixing performance, dual-frequency BDS-2+BDS-3 (B1I/B3I) and dual-frequency GPS (L1L2) have the highest ambiguity fixing rate. The ambiguity fixing rate of dual-frequency BDS-3 (B1C/B2a) and triple-frequency BDS-3 (B1C/B2a/B3I) can be higher than 90% within 100 km. In the case of positioning using only the BDS-3 system, the triple-frequency BDS-3 (B1C/B2a/B3I) is superior to both the dual-frequency BDS-3 (B1I/B3I) and dual-frequency BDS-3 (B1C/B2a) in terms of both positioning accuracy and ambiguity fixing rate. The BDS-2+BDS-3 (B1I/B3I) dual-frequency RTK, which has reached a level comparable to GPS, can provide global users with real-time centimeter-level differential positioning services.
Spatiotemporal Changes and Driver Analysis of Ecosystem Respiration in the Tibetan and Inner Mongolian Grasslands
Authors: Liu Weihua , He Honglin , Wu Xiaojing , Ren Xiaoli , Zhang Li , Zhu Xiaobo , Feng Lili , Lv Yan , Chang Qingqing , Xu Qian , Zhang Mengyu , Zhang Yonghong , Wang Tianxiang
Published: July 2022

Ecosystem respiration (RE) plays a critical role in terrestrial carbon cycles, and quantification of RE is important for understanding the interaction between climate change and carbon dynamics. We used a multi-level attention network, Geoman, to identify the relative importance of environmental factors and to simulate spatiotemporal changes in RE in northern China’s grasslands during 2001–2015, based on 18 flux sites and multi-source spatial data. Results indicate that Geoman performed well (R2 = 0.87, RMSE = 0.39 g C m−2 d−1, MAE = 0.28 g C m−2 d−1), and that grassland type and soil texture are the two most important environmental variables for RE estimation. RE in alpine grasslands showed a decreasing gradient from southeast to northwest, and that of temperate grasslands showed a decreasing gradient from northeast to southwest. This can be explained by the enhanced vegetation index (EVI), and soil factors including soil organic carbon density and soil texture. RE in northern China’s grasslands showed a significant increase (1.81 g C m−2 yr−1) during 2001–2015. The increase rate of RE in alpine grassland (2.36 g C m−2 yr−1) was greater than that in temperate grassland (1.28 g C m−2 yr−1). Temperature and EVI contributed to the interannual change of RE in alpine grassland, and precipitation and EVI were the main contributors in temperate grassland. This study provides a key reference for the application of advanced deep learning models in carbon cycle simulation, to reduce uncertainties and improve understanding of the effects of biotic and climatic factors on spatiotemporal changes in RE.
Evaluation of 10-Year NOAA/NASA Suomi NPP and NOAA-20 VIIRS Reflective Solar Band (RSB) Sensor Data Records (SDR) over Deep Convective Clouds
Authors: Wang Wenhui , Cao Changyong , Shao Xi , Blonski Slawomir , Choi Taeyoung , Uprety Sirish , Zhang Bin , Bai Yan
Published: July 2022

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument onboard the Suomi NPP (S-NPP) and the NOAA-20 satellites that provides state-of-the-art Earth observations for ocean, land, aerosol, and cloud applications. VIIRS Reflective Solar Band (RSB) Sensor Data Records (SDR, or Level 1b products) are calibrated and produced independently by The National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) VIIRS science teams. Multiple versions of S-NPP and NOAA-20 VIIRS SDRs are available to date. This study evaluates the long-term calibration stability, biases, and inter-channel consistency of S-NPP and NOAA-20 VIIRS SDRs generated by NOAA and NASA over Deep Convective Clouds (DCC) to support downstream applications, especially climate data record studies. Five VIIRS RSB SDRs were analyzed in this study: (1) NOAA version 2 S-NPP VIIRS reprocessed SDRs (NOAA-NPP-V2, 2012–2020), (2) NASA Collection 1 S-NPP VIIRS SDRs (NASA-NPP-C1, 2012–2021), (3) NASA Collection 2 S-NPP VIIRS SDRs (NASA-NPP-C2, 2012–2021), (4) NOAA constant F-factor calibrated NOAA-20 VIIRS SDRs (NOAA-N20-ConstF, 2018–2021), and (5) NASA Collection 2 NOAA-20 VIIRS SDRs (NASA-N20-C2, 2018–2021). The DCC time series analysis results indicate that the calibrations of the three S-NPP VIIRS RSB SDRs are generally stable, with trends within ±0.1%/year for all RSBs, except for M3–M4 (all three S-NPP SDRs) and I3 (NASA-NPP-C1 only). The calibration of NASA-NPP-C2 SDRs is more uniform at individual detector levels. NOAA-NPP-V2 and NASA-NPP-C1 SDRs exhibit non-negligible time-dependent detector level degradation in M1–M4 (up to 1.5% in 2020–2021), causing striping in the SDR imagery. The biases between NOAA and NASA S-NPP VIIRS RSB SDRs are from 0.1% to 2.4%. The calibrations of the two NOAA-20 VIIRS RSB SDRs are also generally stable, with trends within ±0.16%/year. Small downward trends were observed in the visible and near-infrared (VIS/NIR) bands, and small upward trends were observed in the shortwave infrared (SWIR) bands for both NOAA and NASA NOAA-20 SDRs. The biases between NOAA and NASA NOAA-20 VIIRS RSB SDRs are nearly constant over time and within ±0.2% for VIS/NIR bands and ±0.7% for SWIR bands. There exists large inter-satellite biases between S-NPP and NOAA-20 VIIRS SDRs, especially in the VIS/NIR bands (up to 4.5% for NOAA SDRs and up to 7% for NASA SDRs). In addition, the DCC reflectance of S-NPP VIIRS RSB spectral bands is more consistent with that of the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) than that of NOAA-20. Bands M4 and M9 seem out of family in all five S-NPP and NOAA-20 RSB SDRs evaluated.
Identifying Land-Use Related Potential Disaster Risk Drivers in the Ayeyarwady Delta (Myanmar) during the Last 50 Years (1974–2021) Using a Hybrid Ensemble Learning Model
Authors: Vogel Anissa , Seeger Katharina , Brill Dominik , Brückner Helmut , Khin Khin Soe  , Nay Win Oo  , Nilar Aung  , Zin Nwe Myint  , Kraas Frauke
Published: July 2022

Land-use and land-cover change (LULCC) dynamics significantly impact deltas, which are among the world’s most valuable but also vulnerable habitats. Non-risk-oriented LULCCs can act as disaster risk drivers by increasing levels of exposure and vulnerability or by reducing capacity. Making thematically detailed long-term LULCC data available is crucial to improving understanding of those dynamics interlinked at different spatiotemporal scales. For the Ayeyarwady Delta, one of the least studied mega-deltas, such comprehensive information is still lacking. This study used 50 Landsat and Sentinel-1A images spanning five decades from 1974 to 2021 in five-year intervals. A hybrid ensemble model consisting of six machine-learning classifiers was employed to generate land-cover maps from the images, achieving accuracies of about 90%. The major identified potential risk-relevant LULCC dynamics include urban growth towards low-lying areas, mangrove deforestation, and the expansion of irrigated agricultural areas and cultivated aquatic surfaces. The novel area-wide LULCC products achieved through the analyses provide a basis to support future risk-sensitive development decisions and can be used for regionally adapted disaster risk management plans and models. Developed with freely available data and open-source software, they hold great potential to increase research activity in the Ayeyarwady Delta and will be shared upon request.
Infrared Small-Target Detection Based on Radiation Characteristics with a Multimodal Feature Fusion Network
Authors: Wu Di , Cao Lihua , Zhou Pengji , Li Ning , Li Yi , Wang Dejun
Published: July 2022

Infrared small-target detection has widespread influences on anti-missile warning, precise weapon guidance, infrared stealth and anti-stealth, military reconnaissance, and other national defense fields. However, small targets are easily submerged in background clutter noise and have fewer pixels and shape features. Furthermore, random target positions and irregular motion can lead to target detection being carried out in the whole space–time domain. This could result in a large amount of calculation, and the accuracy and real-time performance are difficult to be guaranteed. Therefore, infrared small-target detection is still a challenging and far-reaching research hotspot. To solve the above problem, a novel multimodal feature fusion network (MFFN) is proposed, based on morphological characteristics, infrared radiation, and motion characteristics, which could compensate for the deficiency in the description of single modal characteristics of small targets and improve the recognition precision. Our innovations introduced in the paper are addressed in the following three aspects: Firstly, in the morphological domain, we propose a network with the skip-connected feature pyramid network (SCFPN) and dilated convolutional block attention module integrated with Resblock (DAMR) introduced to the backbone, which is designed to improve the feature extraction ability for infrared small targets. Secondly, in the radiation characteristic domain, we propose a prediction model of atmospheric transmittance based on deep neural networks (DNNs), which predicts the atmospheric transmittance effectively without being limited by the complex environment to improve the measurement accuracy of radiation characteristics. Finally, the dilated convolutional-network-based bidirectional encoder representation from a transformers (DC-BERT) structure combined with an attention mechanism is proposed for the feature extraction of radiation and motion characteristics. Finally, experiments on our self-established optoelectronic equipment detected dataset (OEDD) show that our method is superior to eight state-of-the-art algorithms in terms of the accuracy and robustness of infrared small-target detection. The comparative experimental results of four kinds of target sequences indicate that the average recognition rate Pavg is 92.64%, the mean average precision (mAP) is 92.01%, and the F1 score is 90.52%.
Full-Coverage PM2.5 Mapping and Variation Assessment during the Three-Year Blue-Sky Action Plan Based on a Daily Adaptive Modeling Approach
Authors: He Weihuan , Zhang Songlin , Meng Huan , Han Jie , Zhou Gaohui , Song Hongquan , Zhou Shenghui , Zheng Hui
Published: July 2022

Owing to a series of air pollution prevention and control policies, China’s PM2.5 pollution has greatly improved; however, the long-term spatial contiguous products that facilitate the analysis of the distribution and variation of PM2.5 pollution are insufficient. Due to the limitations of missing values in aerosol optical depth (AOD) products, the reconstruction of full-coverage PM2.5 concentration remains challenging. In this study, we present a two-stage daily adaptive modeling framework, based on machine learning, to solve this problem. We built the annual models in the first stage, then daily models were constructed in the second stage based on the output of the annual models, which incorporated the parameter and feature adaptive tuning strategy. Within this study, PM2.5 concentrations were adaptively modeled and reconstructed daily based on the multi-angle implementation of atmospheric correction (MAIAC) AOD products and other ancillary data, such as meteorological factors, population, and elevation. Our model validation showed excellent performance with an overall R2 = 0.91 and RMSE = 9.91 μg/m3 for the daily models, along with the site-based cross-validation R2s and RMSEs of 0.86–0.87 and 12–12.33 μg/m3; these results indicated the reliability and feasibility of the proposed approach. The daily full-coverage PM2.5 concentrations at 1 km resolution across China during the Three-Year Blue-Sky Action Plan were reconstructed in this study. We analyzed the distribution and variations of reconstructed PM2.5 at three different time scales. Overall, national PM2.5 pollution has significantly improved with the annual average concentration dropping from 33.67–28.03 μg/m3, which demonstrated that air pollution control policies are effective and beneficial. However, some areas still have severe PM2.5 pollution problems that cannot be ignored. In conclusion, the approach proposed in this study can accurately present daily full-coverage PM2.5 concentrations and the research outcomes could provide a reference for subsequent air pollution prevention and control decision-making.
In Vitro Alpha-Glucosidase and Alpha-Amylase Inhibitory Activities and Antioxidant Capacity of Helichrysum cymosum and Helichrysum pandurifolium Schrank Constituents
Authors: Jadalla Baraa , Moser Justin , Sharma Rajan , Etsassala Ninon , Egieyeh Samuel , Badmus Jelili , Marnewick Jeanine , Beukes Denzil , Cupido Christopher , Hussein Ahmed
Published: July 2022

Diabetes mellitus (DM) is a group of systemic metabolic disorders with a high rate of morbidity and mortality worldwide. Due to the detrimental side effects of the current treatment, there is a great need to develop more effective antidiabetic drugs with fewer side effects. Natural products are a well-known source for the discovery of new scaffolds for drug discovery, including new antidiabetic drugs. The genus Helichrysum has been shown to produce antidiabetic natural products. In this investigation, the methanolic extract of H. cymosum and H. pandurifolium resulted in the isolation and identification of eleven known compounds viz 5,8-dihydroxy-7-methoxy-2-phenyl flavanone (1), pinostrobin (2), dihydrobaicalein (3), glabranin (4), allopatuletin (5), pinostrobin chalcone (6), helichrysetin (7), 5-hydroxy-3,7-dimethoxyflavone (8), 3,5-dihydroxy-6,7,8-trimethoxyflavone (9), 3-O-methylquercetin (10), and 3-methylethergalangin (11). The in vitro bio-evaluation of isolated compounds against alpha-glucosidase showed that 10, 5, and 11 demonstrated the highest alpha-glucosidase inhibitory activity with IC50 values of 9.24 ± 0.4, 12.94 ± 0.2, and 16.00 ± 2.4 μM respectively, followed by 7 and 3 with IC50 values of 18.16 ± 1.2 and 44.44 ± 0.2 μM respectively. However, none of these compounds showed a measurable inhibitory effect on alpha-amylase under the experimental conditions used except compound 10 which showed a poor alpha-amylase inhibitory activity with an IC50 value of 230.66 ± 15.8 μM. Additionally, strong total antioxidant capacities were demonstrated by 10, 5 and 7 in ferric-ion reducing antioxidant power assay (374.34 ± 69.7; 334.37 ± 1.7; 279.93 ± 0.8) µmol AAE/mmol. This is the first scientific report to be carried out on alpha-glucosidase inhibitory activities and antioxidant capacities of H. cymosum constituents and a first report on the isolation and identification of methoxyflavanoids from H. pandurifolium. Our findings suggest that these compounds are promising candidates to inhibit alpha-glucosidase as well as oxidative stress related to diabetes. Results from molecular docking provided insight into the observed in vitro alpha-glucosidase inhibitory activities for 5, 7, 10, and 11. It is envisaged that the isolated phytochemicals from these plants may contribute to the development of hypoglycemic lead compounds with anti-diabetic potential.
Evaluation of Soil Hydraulic Parameters Calculation Methods Using a Tension Infiltrometer
Authors: Kargas George , Koka Dimitrios , Londra Paraskevi A.
Published: July 2022

In the present work, a review for the methodologies that have been proposed to calculate the main soil hydraulic properties, hydraulic conductivity (K) and sorptivity (S), at negative pressure heads near to saturation of the soil using a tension infiltrometer is presented. These hydraulic properties can be calculated either from the analysis of steady flow or from early time observations. In particular, the main steady state methods described here are those of Ankeny et al., Reynolds and Elrick, and White and Sully, which are all based on Wooding’s equation. As for the transient flow, the approaches of Haverkamp et al. (complete, two-, three-, four-, five-terms expansions), Zhang and two different linearization methods are examined for the estimation of S and K. Generally, in steady state methods studied, a sequence of pressure heads is applied on the same disc (Ankeny et al., Reynolds and Elrick) or a unique pressure head is applied on a single disc radius (White and Sully), while in transient methods, a unique pressure head is applied on a single disc radius (Zhang and Haverkamp et al.). The conditions of their application and the way of calculating the soil parameters included into each method are critically commented. This gives to the researchers the opportunity to choose the appropriate method and a way to analyze the experimental data.
Chemistry of Hydrogen Peroxide Formation and Elimination in Mammalian Cells, and Its Role in Various Pathologies
Authors: Andrés Celia María Curieses , Pérez de la Lastra José Manuel , Juan Celia Andrés , Plou Francisco J. , Pérez-Lebeña Eduardo
Published: July 2022

Hydrogen peroxide (H2O2) is a compound involved in some mammalian reactions and processes. It modulates and signals the redox metabolism of cells by acting as a messenger together with hydrogen sulfide (H2S) and the nitric oxide radical (•NO), activating specific oxidations that determine the metabolic response. The reaction triggered determines cell survival or apoptosis, depending on which downstream metabolic pathways are activated. There are several ways to produce H2O2 in cells, and cellular systems tightly control its concentration. At the cellular level, the accumulation of hydrogen peroxide can trigger inflammation and even apoptosis, and when its concentration in the blood reaches toxic levels, it can lead to bioenergetic failure. This review summarizes existing research from a chemical perspective on the role of H2O2 in various enzymatic pathways and how this biochemistry leads to physiological or pathological responses.
Electricity Price Instability over Time: Time Series Analysis and Forecasting
Authors: Wang Diankai , Gryshova Inna , Kyzym Mykola , Salashenko Tetiana , Khaustova Viktoriia , Shcherbata Maryna
Published: July 2022

Competition in electricity markets leads to volatile conditions which cause persistent price fluctuations over time. This study explores the problem of electricity pricing fluctuations in the DE-LU bidding zone from October 2018 to March 2022 by applying time series analysis. The determinants of electricity price fluctuations are broken down into three groups: exogenous prices (gas, coal and CO2 prices), internal (consumption and generation) and external (net import between neighboring bidding zones) electricity flows. Based on the SARIMAX model, we tried to combine all these factors to forecast electricity prices in the single bidding zone. It was found that the SARIMAX (1, 1, 2) × (3, 1, 0, 7) model with exogenous prices, internal and external electricity flows, which has the lowest AIC and MAPE values, is the best-fitted model for the DE-LU bidding zone. Anonymous trading and unpredictable individual bidding strategies lead to persistent price volatility, which causes electricity prices to deviate from fundamental trends. To reveal the risk factors, the SARIMAX model of electricity prices needs to be supplemented with a GARCH model of the residual returns. For forecasting electricity price residual volatility in the DE-LU bidding zone, the SARIMAX model with exogenous prices, internal and external electricity flows must be accompanied with the GARCH (7, 0) model.
Livelihood Impacts of Large-Scale Agricultural Investments Using Empirical Evidence from Shashamane Rural District of Oromia Region, Ethiopia
Authors: Alemu Yideg , Tolossa Degefa
Published: July 2022

The impact of Large Scale Agricultural Investments (LSAI) on local people’s livelihood improvement has received less attention than it deserves in Ethiopia in general, and the Oromia regional states in particular. The main objective of this study was to analyze the impact of LSAI, which began operations in 2008, on 10,000 hectares of fertile land in the Shashamane rural district of Oromia region, Ethiopia to enhance the quality of life of the local people. A quasi-experimental study design strategy was used to achieve this goal. We obtained primary data from 300 households, comprising 134 treatment homes (households in a community with LSAI) from the Shashamane rural district and 166 control households (households in a community without LSAI) from the Shala district using systematic random sampling. Analysis was undertaken using principal component analysis (PCA) and propensity score matching (PSM). The Sustainable Livelihoods Framework (SLF) was used to examine the theoretical concept with empirical findings. According to the Average Treatment Effect on Treated (ATT) results, the treated households’ natural, human, and financial capital were −0.91, −0.81, and −0.15 less than control families, respectively. Loss of household livelihoods has deepened and exacerbated local poverty. Businesses have not mechanized and controlled these sizable portions of the parcel; instead, peasants have worked on them and exploited the idle parcel. The research suggests that the government’s pro-LSAI investment policy is desirable. However, weak institutional frameworks for protecting local people’s livelihoods as well as LSAI malpractice and the lack of continuous follow-up are causing the LSAI policy to fail. To mitigate the negative impact of LSAI on peasants, it is necessary to consider the local people’s livelihoods, responsive institutions, and accountable ventures.
Research on Extension Design of Emergency Cold Chain Logistics from the Perspective of Carbon Constraints
Authors: Lu Lin , Hu Song , Ren Yuelin , Kang Kai , Li Beibei
Published: July 2022

Extenics has unique advantages in solving contradictions by using formal models to explore the possibility of expanding things and the laws and methods of development and innovation. This paper studies the specific application of the extension strategy generation method in emergency cold chain logistics, in order to solve the problem that the emergency plan is difficult to cover in the face of an emergency. The purpose of this paper is to provide ideas for the generation of strategies to solve the contradictions of cold chain logistics in complex emergency scenarios. Giving full play to the unique advantages of extenics in solving contradictory problems, this paper analyzes the core problems, objectives and conditions of emergency cold chain logistics in four links with the case scenario of the COVID-19 pandemic outbreak, extends and generates 10 measures to form 36 schemes, and evaluates the combination schemes quantitatively and objectively using the dependent function and superiority evaluation formula. In addition, the consideration of carbon constraints is added to the selection of the scheme, and the specific plan of integrating e-commerce platform, expert guidance, establishing temporary cold storage transfer and contactless distribution is designed. The research results provide support for meeting the needs of emergency logistics schemes in different situations and optimizing the energy efficiency of the scheme while ensuring humanitarian support. At the same time, the application of extenics basic-element formal language also provides a reference for further applying artificial intelligence to the design of emergency logistics schemes.
Performance Loss Rates of a 1 MWp PV Plant with Various Tilt Angle, Orientation and Installed Environment in the Capital of Cyprus
Authors: Karahüseyin Turgut , Abbasoğlu Serkan
Published: July 2022

Evolution from fossil fuel sources to environmentally friendly and sustainable energy sources is one of the key aspects of the energy transition goal. On the other hand, Solar Photovoltaic systems are the most promising and improving technologies in the energy market However, it is well known that the performance of PV panels decreases in the process of time. This paper focuses on analyzing the performance loss rates (PLR) of mid-scale crystalline silicon (c-Si) PV systems of the same manufacturer with different orientations and tilt angles in the same region for the duration of four years of outdoor exposure. Three commonly used statistical methods are deployed to calculate PLRs; seasonal and trend decomposition using locally weighted scatterplot smoothing (STL), classical seasonal decomposition (CSD) and year on year (YoY) methods coupled with various performance metrics, namely Performance ratio (PR), temperature corrected performance ratio TCPR) and weather corrected performance ratio suggested by National Renewable Energy Laboratory (NRELPR). It is found that PLRs of analyzed venues, Arazi, Arena and Stonite, with the YOY approach are −1.2%/year, −0.73%/year and −2.65%/year, respectivelty., respectively. Furthermore, STL method demonstrated PLRs of −0.69%/year, −0.65%/year and −2.91%/year, respectively. On the other hand, the CSD method generated positive PLRs for some inverters while aforementioned statistical approaches proposed PLRs close to −2%/year, making the CSD method inappropriate for use under a heavy soiling environment. Within two km distance, variations up-to four-fold in PLRs are recorded between the venues during analyzed period. Furthermore, variations in PLRs are more dependent on the statistical approach rather than the performance metric.
Tools and Technologies for Sustainable Territorial Development in the Context of a Quadruple Innovation Helix
Authors: Parygin Danila , Sadovnikova Natalia , Gamidullaeva Leyla , Finogeev Anton , Rashevskiy Nikolay
Published: July 2022

The study of the problem of sustainable development of urban areas led to the understanding of the important role that population involvement plays in solving the issues related to forming a comfortable urban environment. It is normal practice to take into account the proposals and recommendations of citizens and organizations when making decisions in the field of territorial development. Nevertheless, the implementation of participatory governance mechanisms faces significant difficulties. This is primarily due to the lack of effective tools for analyzing the opinion of citizens and technologies for integrating urban communities into existing institutions of governance. This article discusses the ways of organizing expert polls based on the principles of “Socratic dialogue”. The idea of using social networks for testing and promoting urban development projects by analyzing social reactions to various urban initiatives is considered. The possibility of predicting public opinion about a specific solution for urban development using historical data from social networks has been investigated. An approach to the gamification of work with a social response to the urban environment state through virtual interactions with infrastructure objects is proposed. The prospects for gamification to motivate civic participation and improve the efficiency of feedback mechanisms between the city and its residents are discussed.
Assessment and Prediction of Grain Production Considering Climate Change and Air Pollution in China
Authors: Wang Hengli , Liu Hong , Ma Rui
Published: July 2022

This study examines the spatial and temporal impacts of climate change on grain production in China. This is achieved by establishing a spatial error model consisting of four indicators: the climate, air pollution, economic behavior, and agricultural technology, covering 31 provinces in China from 2004 to 2020. These indicators are used to validate the spatial impacts of climate change on grain production. Air pollution data are used as instrumental variables to address the causality between climate and grain production. The regression results show that: First, climatic variables all have a non-linear “increasing then decreasing” effect on food production. Second, SO2, PM10, and PM2.5 have a negative impact on grain production. Based on the model, changes in the climatic production potential of grain crops can be calculated, and the future spatial layout of climate production can also be predicted by using random forests. Studies have shown that the median value of China’s grain production potential is decreasing, and the low value is increasing.
Mechanism Analysis of Roof Deformation in Pre-Driven Longwall Recovery Rooms Considering Main Roof Failure Form
Authors: Wang Bonan , Mu Lin , He Mingming , Gu Shuancheng
Published: July 2022

Pre-driven recovery rooms are used extensively for the removal of mining equipment and hydraulic supports in longwall coal mining. Roof stability is a crucial factor influencing the speed and safety of the removal of operators in pre-driven recovery rooms. The characterization of roof deformation mechanisms in recovery rooms under front abutment pressures is significant for surrounding rock control and stability evaluation. In this study, three different roof subsidence evaluation models, considering different main roof failure forms, were established. It was noticed that the main roof break position had a significant effect on recovery room roof sag. The breaking of the main roof above the main recovery room and protective coal pillar was found to be the main driving force for large roof deformations. Furthermore, field monitoring data of roof sag and coal pillar stress in the 15205 and 15206 panels of Hongliulin Coal Mine were analyzed. According to evaluation models and field monitoring data, we propose determination methods for the evaluation of recovery room roof sag and main roof break position. During the study it was found that the inversion results of the main roof break position of the recovery room in 15205 and 15206 panels were 4.2 m and 9.1 m, respectively, which are basically consistent with the results calculated by periodic weighting. The research findings provide a reference for the quantitative evaluation of recovery room roof stability and the design of support parameters and yield mining.
Investigation of Spatio–Temporal Changes in Land Use and Heat Stress Indices over Jaipur City Using Geospatial Techniques
Authors: Chandra Suresh , Dubey Swatantra Kumar , Sharma Devesh , Mitra Bijon Kumer , Dasgupta Rajarshi
Published: July 2022

Heat waves are expected to intensify around the globe in the future, with a potential increase in heat stress and heat-induced mortality in the absence of adaptation measures. India has high current exposure to heat waves, and with limited adaptive capacity, impacts of increased heat waves might be quite severe. This paper presents a comparative analysis of urban heat stress/heatwaves by combining temperature and vapour pressure through two heat stress indices, i.e., Wet Bulb Globe Temperature (WBGT) and humidex index. For the years 1970–2000 (historical) and 2041–2060 (future), these two indicators were estimated in Jaipur. Another goal of this research is to better understand Jaipur land use changes and urban growth. For the land use study, Landsat 5 TM and Landsat 8 OLI satellite data from the years 1993, 2010, and 2015 were examined. During the research period, urban settlement increased and the majority of open land is converted to urban settlements. In the coming term, all months except three, namely July to September, have seen an increase in the WBGT index values; however, these months are classified as dangerous. Humidex’s historical value has been 21.4, but in RCP4.5 and RCP8.5 scenarios, it will rise to 25.5 and 27.3, respectively, and slip into the danger and extreme danger categories. The NDVI and SAVI indices are also used to assess the city’s condition during various periods of heat stress. The findings suggest that people’s discomfort levels will rise in the future, making it difficult for them to work outside and engage in their usual activities.
Highway Proneness Appraisal to Landslides along Taiping to Ipoh Segment Malaysia, Using MCDM and GIS Techniques
Authors: Yamusa Idris Bello , Ismail Mohd Suhaili , Tella Abdulwaheed
Published: July 2022

Landslides are geological hazards that claim lives and affect socio-economic growth. Despite increased slope failure, some constructions, such as road constructions, are still being performed without proper investigation of the susceptibility of slope mass movement. This study researches the susceptibility of landslides in a study area encompassing a major highway that extends from Taiping to Ipoh, Malaysia. After a comprehensive literature review, 10 landslide conditioning factors were considered for this study. As novel research in this study area, multi-criteria decision-making (MCDM) models such as AHP and fuzzy AHP were used to rank the conditioning factors before generating the final landslide susceptibility mapping using Geographical Information System (GIS) software. The landslide susceptibility map has five classes ranging from very low (9.20%) and (32.97%), low (18.09%) and (25.60%), moderate (24.46%) and (21.36%), high (27.57%) and (13.26%), to very high (20.68%) and (6.81%) susceptibility for the FAHP and AHP models, respectively. It was recorded that the area is mainly covered with moderate to very high landslide risk, which requires proper intervention, especially for subsequent construction or renovation processes. The highway was overlayed on the susceptibility map, which concludes that the highway was constructed on a terrain susceptible to slope instability. Therefore, decision-makers should consider further investigation and landslide susceptibility mapping before construction.
The Effects of Innovation Adoption and Social Factors between Sustainable Supply Chain Management Practices and Sustainable Firm Performance: A Moderated Mediation Model
Authors: Sharafuddin Mohammed Ali , Madhavan Meena , Chaichana Thanapong
Published: July 2022

The aim of this study was to develop higher-order scales for assessing sustainable supply chain management practices, innovation adoption, and sustainable firm performance in the restaurant sector. Three different higher-order scales were developed for assessing the SSCM, SFP and innovation adoption. The first scale for SSCM higher-order construct consisted of service–product supply chain management practices (SPSSCM), service–setting supply chain management practices (SSSSCM), and service–delivery supply chain management practices (SDSSCM). The second higher-order scale for sustainable firm performance (SFP) consisted of economic, operational, environmental, and socio-cultural performance. The third higher-order scale for innovation adoption (INNO) consisted of “product- and process-based innovation”, “marketing-based innovation”, “technology-based innovation” and “organizational innovation”. The face, content, construct, convergent, and discriminant validity was tested using pilot study, expert opinion, EFA, and CFA. With 178 responses collected from restaurateurs, managers, and supervisors of casual restaurants in Prachuap Khiri Khan province in Thailand, this study evaluates the direct effects of SSCM on SFP. It further evaluates the mediating role of innovation adoption between sustainable supply chain management practices and firm performance and the moderated mediation effects of socio-demographic factors such as age, gender, education, and experience. The results reveal that sustainable supply chain management practices can positively lead to sustainable firm performance. However, irrespective of the indirect effects of socio-demographic factors, adopting innovation completely mediates the relationship between sustainable supply chain management practices and firm performance.