bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of zero tillage maize production on yield, income, and resource utilization in peninsular India: an action-based quasi-experimental research
Authors: Dey Shiladitya , Abbhishek Kumar , Saraswathibatla Suman , Singh Piyush Kumar , Kuntamalla Sreedhar , Bommaraboyina Prithvi Ram , Raj Abhishek , Kaliki Hamika , Choubey Abhishek Kumar , Rongali Hari Babu , Upamaka Aruna
Published: May 2024

Purpose

The present study aims to identify the crucial determinants of the adoption of zero-tillage (ZT) technology in maize production in peninsular India. The study also measures the impact of ZT adoption on maize yield, income generation, and the expenses associated with different agricultural operations.

Methodology

The study used multi-stage stratified random sampling and conducted a face-to-face questionnaire survey to collect primary data from 1,189 maize farmers. Initially, the study employed probit regression analysis to identify the ZT adoption determinants. Subsequently, using the Propensity Score Matching (PSM) approach, the study measures the impact of ZT adoption over conventional tillage in terms of yield, income, and cost management. Finally, the Endogenous Switch Regression (ESR) method was implemented to mitigate unobserved heterogeneity and sample selection bias. Additionally, ESR assessed the robustness of PSM results.

Findings

The probit model identifies that variables like education, institutional credit adoption, crop insurance, visit of extension agent, landholding size, and prior experience of new technology adoption positively influence ZT adoption. The PSM and ESR approach results suggest that ZT adoption positively impacts farmers’ yield and net income while reducing cultivation costs and labor use. Results show that ZT adoption decreases the cost of land preparation, weed, pest management, and harvesting by INR 2708 acre−1, INR 167 acre−1, and INR 649 acre−1, respectively, thereby decreasing the overall cultivation cost by INR 8376 acre−1. However, seed and seed treatment costs and irrigation costs improve by INR 108 acre−1 and 176 acre−1 due to the adoption of ZT in maize cultivation. Moreover, ZT improves maize yield by 2.53 quintal acre−1 and minimises 9.56 person-days acre−1. ESR results suggest that the net return from maize cultivation is 26.1% higher for ZT adopters than conventional farmers. Additionally, ZT adopters can save 8.23 man-days acre−1, providing additional monetary benefits of INR 3259 acre−1 compared to ZT non-adopters.

Practical implications

The study findings may support policymakers in designing suitable agricultural policies to improve technology adoption and motivate small and marginal maize farmers for sustainable production.
The impacts of precision livestock farming tools on the greenhouse gas emissions of an average Scottish dairy farm
Authors: Ferguson H. J. , Bowen J. M. , McNicol L. C. , Bell J. , Duthie C-A. , Dewhurst R. J.
Published: May 2024

Precision livestock farming (PLF) tools are increasingly used in daily herd management to improve health, welfare, and overall production. While not intended to reduce greenhouse gas (GHG) emissions on farm, PLF tools can do so indirectly by improving overall efficiency, thereby reducing the emissions per unit of product. This work modelled the potential effects of commercially available PLF tools on whole enterprise and product emissions of two average Scottish dairy farm systems (an 8,000 L and 10,000 L herd) using the Agrecalc carbon footprinting tool. Scenarios modelled included an improvement in fertility and an improvement in fertility and yield from the introduction of an accelerometer-based sensor, and an improvement in health from introduction of an accelerometer-based sensor, with and without the use of management interventions. Use of a sensor intended to improve fertility had the largest reduction in total emissions (kg CO2e) of −1.42% for a 10,000 L farm, with management changes applied. The largest reduction in emissions from milk production (kg CO2e) of −2.31% was observed via fertility technology application in an 8,000 L farm, without management changes. The largest reduction in kg CO2e per kg fat and protein corrected milk of −6.72% was observed from an improvement in fertility and yield in a 10,000 L herd, with management changes. This study has highlighted the realistic opportunities available to dairy farmers in low and high input dairy systems to reduce their emissions through adoption of animal mounted PLF technologies.
Gp85 protein encapsulated by alginate-chitosan composite microspheres induced strong immunogenicity against avian leukosis virus in chicken
Authors: Lei Tianyu , Liu Rongchang , Zhuang Liyun , Dai Tingting , Meng Qingfu , Zhang Xiaodong , Bao Yinli , Huang Cuiqin , Lin Weiming , Huang Yu , Zheng Xintian
Published: May 2024

Introduction

Avian leukosis, a viral disease affecting birds such as chickens, presents significant challenges in poultry farming due to tumor formation, decreased egg production, and increased mortality. Despite the absence of a commercial vaccine, avian leukosis virus (ALV) infections have been extensively documented, resulting in substantial economic losses in the poultry industry. This study aimed to develop alginate-chitosan composite microspheres loaded with ALV-J Gp85 protein (referred to as aCHP-gp85) as a potential vaccine candidate.

Methods

Sodium alginate and chitosan were utilized as encapsulating materials, with the ALV-J Gp85 protein serving as the active ingredient. The study involved 45 specific pathogen-free (SPF) chickens to evaluate the immunological effectiveness of aCHP-gp85 compared to a traditional Freund adjuvant-gp85 vaccine (Freund-gp85). Two rounds of vaccination were administered, and antibody levels, mRNA expression of immune markers, splenic lymphocyte proliferation, and immune response were assessed. An animal challenge experiment was conducted to evaluate the vaccine’s efficacy in reducing ALV-J virus presence and improving clinical conditions.

Results

The results demonstrated that aCHP-gp85 induced a significant and sustained increase in antibody levels compared to Freund-gp85, with the elevated response lasting for 84 days. Furthermore, aCHP-gp85 significantly upregulated mRNA expression levels of key immune markers, notably TNF-α and IFN-γ. The application of ALV-J Gp85 protein within the aCHP-gp85 group led to a significant increase in splenic lymphocyte proliferation and immune response. In the animal challenge experiment, aCHP-gp85 effectively reduced ALV-J virus presence and improved clinical conditions compared to other groups, with no significant pathological changes observed.

Discussion

The findings suggest that aCHP-gp85 elicits a strong and prolonged immune response compared to Freund-gp85, indicating its potential as an innovative ALV-J vaccine candidate. These results provide valuable insights for addressing avian leukosis in the poultry industry, both academically and practically.
Case report: Magnetic resonance imaging features with postoperative improvement of atypical cervical glioma characterized by predominant extramedullary distribution in a dog
Authors: Kim Junyoung , Kim Kihoon , Chung Dai Jung , Kim Yebeen , Kim Kitae , Oh Dayoung , Lee Namsoon , Choi Jihye , Yoon Junghee
Published: May 2024

Introduction

Intramedullary cord tumors present diagnostic and therapeutic challenges. Furthermore, spinal cord tumors can move across compartments, making antemortem diagnosis difficult, even with advanced imaging. This report presents a rare case of a cranial cervical spinal glioma, confirmed by surgical histopathology, with postoperative improvement in a dog.

Case description

A 9-year-old female Maltese dog presented with kyphotic posture, progressive left hemiparesis, and decreased appetite. Neurological examination revealed neck pain and decreased proprioception in the left limbs along with intact deep pain perception. Two days later, the patient developed non-ambulatory tetraparesis. Magnetic resonance imaging (MRI) revealed an ovoid, well-defined mass with homogeneously marked contrast enhancement in the second cervical spinal cord that severely compressed the spinal cord. This mass was heterogeneously hyperintense on T2-weighted images and iso-to-hypointense on T1-weighted images, showing an appearance resembling the “golf-tee” and “dural tail” signs. The MRI findings suggested an intradural extramedullary tumor. Intraoperatively, a well-demarcated mass which was locally adherent to the spinal meninges was removed. Both histopathological and genomic tumor tests were indicative of a glioma. Approximately 2 weeks postoperatively, the patient’s neurological signs returned to normal.

Conclusion

This case report describes an atypical cervical glioma with complicated MR characteristics in a dog, where MRI helped guide surgical intervention.
Allele frequency of a genetic risk variant for necrotizing meningoencephalitis in pug dogs from Europe and association with the clinical phenotype
Authors: van Renen Jana , Kehl Alexandra , Buhmann Gesine , Matiasek Lara A. , Zablotski Yury , Fischer Andrea
Published: May 2024

Introduction

Necrotizing meningoencephalitis (NME) in pugs is a potentially fatal disease, which needs lifelong treatment with immunosuppressive or immunomodulatory drugs and shares parallels with acute fulminating multiple sclerosis. Genetic variants of the DLA class II gene are associated with an increased risk for NME. Genetic testing is recommended prior to breeding. The aim of this study was to describe the current allele frequency of a previously identified NME risk variant in the European pug population. A secondary aim was to investigate the association of the NME risk variant with the clinical phenotype in pugs.

Methods

Results of genetic testing for the CFA12:2605517delC variant in European pugs between 2012 and 2020 were retrieved (n = 5,974). A validated questionnaire was mailed to all submitters of samples for further information on neurological signs, diagnostic tests, and disease course.

Results

The allele frequency of the CFA12 NME risk variant was 25.7% in the European pug population dogs; 7.4% of the dogs were homozygous and 36.7% were heterozygous for the NME risk variant on CFA12. Completed questionnaires were available in 203 dogs including 25 dogs with epileptic seizures or other neurological signs. The clinical phenotype was consistent with NME in 3.9% with a median age of onset of 1.0 years, and indicative of idiopathic epilepsy in 2.9% with a median onset of 2.5 years. Eleven dogs remained unclassified. Pugs with the NME phenotype were significantly more frequently homozygous for the NME risk variant on CFA12 compared to pugs ≥6 years without neurological signs or seizures (p = 0.008).

Discussion

The CFA12:2605517delC genetic risk variant is widely distributed in the European pug population and frequently homozygous in pugs with a NME phenotype. The data support the clinical relevance of the CFA12:2605517delC genetic risk variant.
Influence of Exogenous Abscisic Acid on Germination and Physiological Traits of Sophora viciifolia Seedlings under Drought Conditions
Authors: Rao Xin , Zhang Yujun , Gao Yang , Zhao Lili , Wang Puchang
Published: May 2024

This study investigates the role of abscisic acid (ABA) in bolstering drought resistance in plants, employing “Panjiang Sophora viciifolia” as the subject. A simulated drought scenario was created using polyethylene glycol (PEG-6000) to examine the impact of varying drought intensities (0%, 5%, 20% PEG) and ABA concentrations (0, 10, 50, 100, 200 mg·L−1) on the germination and physiological parameters of Sophora viciifolia. The results showed that in the absence of ABA, the germination rate (GR), germination potential (GP), and germination index (GI) of S. viciifolia seeds initially increased and then decreased with escalating PEG-induced drought stress. At PEG-induced drought stress levels of 5% and 20%, the activities of peroxidase (POD) and catalase (CAT), along with the malondialdehyde (MDA) content, were significantly higher than in the control (CK) (p < 0.05). In response to drought stress, S. viciifolia seeds adapted by modulating germination behavior, augmenting the content of osmoregulatory substances, and boosting the activity of protective enzymes. The addition of ABA markedly enhanced GR, GE, GI, activities of POD, superoxide dismutase (SOD), and CAT, as well as the levels of MDA and proline (Pro) under drought conditions (p < 0.05). Relative to CK, low ABA concentrations (10–100 mg·L−1) resulted in increased GR, GP, GI, POD, SOD, CAT, MDA, and Pro levels; whereas, at a higher concentration (200 mg·L−1), although GR, GP, and GI decreased, POD, SOD, CAT, MDA, and Pro levels increased. Through principal component analysis and membership function comprehensive evaluation, it was determined that administering 50 mg·L−1 ABA was most effective in enhancing drought resistance in S. viciifolia seedlings.
A Prediction Model of Marine Geomagnetic Diurnal Variation Using Machine Learning
Authors: Xiong Pan , Bian Gang , Liu Qiang , Jin Shaohua , Yin Xiaodong
Published: May 2024

Geomagnetic diurnal variation significantly influences the precision of marine magnetic measurements. Precise estimation of this variation is crucial for enhancing the accuracy of offshore magnetic surveys. To address the challenges in achieving the desired accuracy with current estimation methods for geomagnetic diurnal variation, this study introduces a high-precision estimation model that integrates support vector machine (SVM) and random forest (RF) techniques. Initially, the data preprocessing phase includes an innovative extreme value adjustment method to rectify the temporal discrepancies across different stations, alongside employing the base period technique for daily baseline correction. Subsequently, we construct models to capture the daily variation trends at various times, facilitating an in-depth analysis of the diurnal variation patterns. The culmination of this process involves employing a fusion model algorithm to compute the diurnal variations across all stations comprehensively. Comparative analyses with conventional methods, such as distance weighting, bifactor weighting, and latitude weighting, reveal that our proposed model achieves a significant reduction in the root mean square error (RMSE) by an average of 31%, decreases the mean absolute error (MAE) by 35%, and enhances the Pearson correlation coefficient by 20% on average. These improvements underscore the superior accuracy of our geomagnetic diurnal variation estimation model.
The Affective Byzantine Book: Reflections on Aesthetics of Gospel Lectionaries
Authors: Kopta Joseph R.
Published: May 2024

The aesthetic qualities of Byzantine Gospel Lectionaries in Middle Byzantine times, afforded by their material construction, fostered an intermedial relationship with the architectural interiors of the churches and chapels where they were used in sacred liturgies. In particular, Byzantine book makers employed discreet reflective materials—particularly albumen and gold—that engendered an aesthetic of liquidity. If we center materiality and aesthetic considerations of the Byzantine Gospel Lectionary, building upon art history’s so-called “material turn”, we can come closer to understanding something of the poetry of the Byzantine manuscript as part of an affective experience—one that was shiny, shimmering, and fluid.
Imaging and Interferometric Mapping Exploration for PIESAT-01: The World’s First Four-Satellite “Cartwheel” Formation Constellation
Authors: Zhang Tian , Qian Yonggang , Li Chengming , Lu Jufeng , Fu Jiao , Guo Qinghua , Guo Shibo , Wang Yuxiang
Published: May 2024

The PIESAT-01 constellation is the world’s first multi-baseline distributed synthetic aperture radar (SAR) constellation with a “Cartwheel” formation. The “Cartwheel” formation is a unique formation in which four satellites fly in companion orbits, ensuring that at any given moment, the main satellite remains at the center, with three auxiliary satellites orbiting around it. Due to this unique configuration of the PIESAT-01 constellation, four images of the same region and six pairs of baselines can be obtained with each shot. So far, there has been no imaging and interference research based on four-satellite constellation measured data, and there is an urgent need to explore algorithms for the “Cartwheel” configuration imaging and digital surface model (DSM) production. This paper introduces an improved bistatic SAR imaging algorithm under the four-satellites interferometric mode, which solves the problem of multi-orbit nonparallelism in imaging while ensuring imaging coherence and focusing ability. Subsequently, it presents an interferometric processing method for the six pairs of baselines, weighted fusion based on elevation ambiguity from different baselines, to obtain a high-precision DSM. Finally, this paper selects the Dingxi region of China and other regions with diverse terrains for imaging and DSM production and compares the DSM results with ICESat-2 global geolocated photon data and TanDEM DSM data. The results indicate that the accuracy of PIESAT-01 DSM meets the standards of China’s 1:50,000 scale and HRTI-3, demonstrating a high level of precision. Moreover, PIESAT-01 data alleviate the reliance on simulated data for research on multi-baseline imaging and multi-baseline phase unwrapping algorithms and can provide more effective and realistic measured data.
Electrical Stimulation of Mesenchymal Stem Cells as a Tool for Proliferation and Differentiation in Cartilage Tissue Engineering: A Scaffold-Based Approach
Authors: Lehmenkötter Nicolas , Greven Johannes , Hildebrand Frank , Kobbe Philipp , Eschweiler Jörg
Published: May 2024

Electrical stimulation (ES) is a widely discussed topic in the field of cartilage tissue engineering due to its ability to induce chondrogenic differentiation (CD) and proliferation. It shows promise as a potential therapy for osteoarthritis (OA). In this study, we stimulated mesenchymal stem cells (MSCs) incorporated into collagen hydrogel (CH) scaffolds, consisting of approximately 500,000 cells each, for 1 h per day using a 2.5 Vpp (119 mV/mm) 8 Hz sinusoidal signal. We compared the cell count, morphology, and CD on days 4, 7, and 10. The results indicate proliferation, with an increase ranging from 1.86 to 9.5-fold, particularly on day 7. Additionally, signs of CD were observed. The stimulated cells had a higher volume, while the stimulated scaffolds showed shrinkage. In the ES groups, up-regulation of collagen type 2 and aggrecan was found. In contrast, SOX9 was up-regulated in the control group, and MMP13 showed a strong up-regulation, indicating cell stress. In addition to lower stress levels, the control groups also showed a more spheroidic shape. Overall, scaffold-based ES has the potential to achieve multiple outcomes. However, finding the appropriate stimulation pattern is crucial for achieving successful chondrogenesis.
Succinimide Derivatives as Acetylcholinesterase Inhibitors—In Silico and In Vitro Studies
Authors: Grodner Błażej , Pisklak Dariusz Maciej , Szeleszczuk Łukasz
Published: May 2024

We studied the effect of succinimide derivatives on acetylcholinesterase activity due to the interest in compounds that influence this enzyme’s activity, which could help treat memory issues more effectively. The following parameters were established for this purpose based on kinetic investigations of the enzyme in the presence of succinimide derivatives: the half-maximal inhibitory concentration, the maximum rate, the inhibition constant, and the Michaelis–Menten constant. Furthermore, computational analyses were performed to determine the energy required for succinimide derivatives to dock with the enzyme’s active site. The outcomes acquired in this manner demonstrated that all compounds inhibited acetylcholinesterase in a competitive manner. The values of the docking energy parameters corroborated the kinetic parameter values, which indicated discernible, albeit slight, variations in the inhibitory intensity among the various derivatives.
Performance of a Composite Inhibitor on Mild Steel in NaCl Solution: Imidazoline, Sodium Molybdate, and Sodium Dodecylbenzenesulfonate
Authors: Wang Xue , Fan Changfeng , Sun Lanyi , Shang Hongyan , Zhang Duxin , Xu Nan , Wang Bin , Xu Jianbin
Published: May 2024

Mild steel corrosion is a significant challenge in oil and gas exploitation. Inhibitors are frequently employed to minimize the corrosive impact on mild steel. Mixing corrosion inhibitors is an effective method in reducing the dosage of toxic compounds and expanding the potential applications of inhibitors in NaCl solutions. Herein, a mixed corrosion inhibitor composed of imidazoline (IM), sodium molybdate, and sodium dodecylbenzenesulfonate (SDBS) for mild steel in a 3.5 wt% NaCl solution are investigated by orthogonal experimental design and electrochemical measurement. The imidazoline compound was synthesized and identified using Fourier transform infrared (FTIR) spectroscopy. The inhibitory effect is improved by higher concentrations of sodium molybdate and is further enhanced with the addition of 10 mg/L of SDBS. The electrochemical impedance spectroscopy indicates that the combination of IM (100 mg/L), sodium molybdate (50 mg/L), and SDBS (100 mg/L) results in excellent performance with electrochemical impedance (1.8 kohm·cm2). The mild steel surfaces after electrochemical measurement were analyzed using scanning electron microscopy (SEM). The information can contribute to the development of corrosion inhibitors with high performance or to understand the influence of mixing inhibitors on corrosion processes of mild steels.
Investigating the Consumption Patterns of Japanese Seafood during the COVID-19 Pandemic
Authors: Aruga Kentaka , Wakamatsu Hiroki
Published: May 2024

The COVID-19 pandemic, with increased home cooking and decreased restaurant dining, significantly altered seafood consumption patterns. By applying an ordered logit model to identify factors affecting seafood consumption during the pandemic, this study found that the shift in seafood consumption was driven by factors such as changes in meal preparation methods, more time spent at home, and shifts in financial situations. While take-out consumption boosted overall seafood intake, popular varieties saw a rise in home consumption, while high-end seafood suffered from decreased demand as consumers focused more on home dining. This study underscores the importance of supporting suppliers, restaurants, and retailers dealing with high-end seafood, as they face economic challenges due to reduced consumption. In summary, pandemic-induced restrictions on mobility led to a notable transition from restaurant-prepared seafood to home-cooked options, highlighting the need for targeted policies to aid affected sectors.
Research on Active Safety Situation of Road Passenger Transportation Enterprises: Evaluation, Prediction, and Analysis
Authors: Zheng Lili , Cao Shiyu , Ding Tongqiang , Tian Jian , Sun Jinghang
Published: May 2024

The road passenger transportation enterprise is a complex system, requiring a clear understanding of their active safety situation (ASS), trends, and influencing factors. This facilitates transportation authorities to promptly receive signals and take effective measures. Through exploratory factor analysis and confirmatory factor analysis, we delved into potential factors for evaluating ASS and extracted an ASS index. To predict obtaining a higher ASS information rate, we compared multiple time series models, including GRU (gated recurrent unit), LSTM (long short-term memory), ARIMA, Prophet, Conv_LSTM, and TCN (temporal convolutional network). This paper proposed the WDA-DBN (water drop algorithm-Deep Belief Network) model and employed DEEPSHAP to identify factors with higher ASS information content. TCN and GRU performed well in the prediction. Compared to the other models, WDA-DBN exhibited the best performance in terms of MSE and MAE. Overall, deep learning models outperform econometric models in terms of information processing. The total time spent processing alarms positively influences ASS, while variables such as fatigue driving occurrences, abnormal driving occurrences, and nighttime driving alarm occurrences have a negative impact on ASS.
Ion-Selective Electrodes in the Food Industry: Development Trends in the Potentiometric Determination of Ionic Pollutants
Authors: Ruiz-Gonzalez Antonio
Published: May 2024

Food quality assessment is becoming a global priority due to population growth and the rise of ionic pollutants derived from anthropogenic sources. However, the current methods used to quantify toxic ions are expensive and their operation is complex. Consequently, there is a need for affordable and accessible methods for the accurate determination of ion concentrations in food. Electrochemical sensors based on potentiometry represent a promising approach in this field, with the potential to overcome limitations of the currently available systems. This review summarizes the current advances in the electrochemical quantification of heavy metals and toxic anions in the food industry using potentiometric sensors. The healthcare impact of common heavy metal contaminants (Cd2+, Hg2+, Pb2+, As3+) and anions (ClO4−, F−, HPO4−, SO42−, NO3−, NO2−) is discussed, alongside current regulations, and gold standard methods for analysis. Sensor performances are compared to current benchmarks in terms of selectivity and the limit of detection. Given the complexity of food samples, the percentage recovery values (%) and the methodologies employed for ion extraction are also described. Finally, a summary of the challenges and future directions of the field is provided. An overview of technologies that can overcome the limitations of current electrochemical sensors is shown, including new extraction methods for ions in food.
Magnetic and Thermal Behavior of a Planar Toroidal Transformer
Authors: Benamer Kahina , Hamid Azzedine , Rossi di Schio Eugenia , Mokhefi Abderrahim , Melati Rabia , Valdiserri Paolo
Published: May 2024

This paper presents a study on the magnetic and thermal behaviors of a planar toroidal transformer, comprising two planar toroidal coils. In our configuration, the primary coil consists of twenty turns, while the secondary coil consists of ten turns. This design combines the advantages of both toroidal and planar transformers: it employs flat coils, akin to those utilized in planar transformers, while retaining a toroidal shape for its magnetic core. This combination enables leveraging the distinctive characteristics of both transformer types. This study delves into electromagnetic and thermal behaviors. Electromagnetic behavior is elucidated through Maxwell’s equations, offering insights into the distribution of magnetic fields, potentials, and electric current densities. Fluid flow is modeled via the Navier–Stokes equations. By coupling these equation sets, a more comprehensive and accurate portrayal of the thermal phenomena surrounding electrical equipment is attained. Such research is invaluable in the design and optimization of electrical systems, empowering engineers to forecast and manage thermal effects more efficiently. Consequently, this aids in enhancing the reliability, durability, and performance optimization of electrical equipment. The mathematical model was solved using the finite element method integrated into the COMSOL Multiphysics software v. 6.0. The COMSOL Multiphysics simulation showed correct behavior of potential, electric field, current density, and uniformly distributed temperature. In addition, this planar toroidal coil transformer model offers many advantages, such as small dimensions, high resonance frequency, and high operating reliability. This study made it possible to identify the range of its optimal functioning.
Pollutant Emissions and Heavy Metal Migration in Co-Combustion of Sewage Sludge and Coal
Authors: Liu Chunyu , Yue Changtao , Ma Yue
Published: May 2024

The treatment of sewage sludge has become a global concern. Large amounts of sewage sludge can be disposed of by burning coal-mixed sludge. Thermogravimetric analysis and lab-scale combustion experiments in a drop tube furnace were utilized to study the combustion characteristics, pollutant emissions, and heavy metal migration during the co-combustion of coal and sewage sludge. The results showed that the blended fuels with a sewage sludge content less than 10 weight percent exhibited coal-like combustion characteristics. Additionally, the additional sewage sludge favored the ignition performance of blended fuels. When sewage sludge was added, the SO2 emissions rose to 76 mg/Nm3 under the 10% sludge condition—nearly three times higher than that of coal alone. While NOx emissions stayed mostly unchanged, HCl and HF emissions were very low. Meanwhile, Cr, Cu, and Ni migrated to the bottom ash, and their concentrations were all reduced with an increase in sewage sludge. Pb, Cd, Cr, Cu, Ni, and Hg migrated to the flue gas, mostly in the form of gaseous components. The results provide crucial information in the co-combustion of sewage sludge and coal, with implications in the development and improvement of large-scale, harmless, and resource-recovering techniques for waste sludge.
Experimental Study on Paraffin Wax and Soya Wax Supported by High-Density Polyethylene and Loaded with Nano-Additives for Thermal Energy Storage
Authors: Yadav Deepak Kumar , Rathore Pushpendra Kumar Singh , Singh Rajeev Kumar , Gupta Arvind Kumar , Sikarwar Basant Singh
Published: May 2024

Thermal energy storage technology has evolved as one of the prominent methods of storing thermal energy when it is available and utilized as per the requirements. In recent years, thermal energy storage has found a variety of applications for thermal management, such as buildings, batteries, electronics, cold storage, textiles, and solar thermal systems. Phase Change Material (PCM) has taken the lead among all other thermal energy storage materials because of various merits such as high energy density, ease of use, low cost, low volume change, environmental friendliness, easy availability, and chemical stability. However, limitations such as poor thermal conductivity and leakage during phase transformation limit their applicability. In this study, Shape Stabilized Composite PCM (SSCPCM) was developed to overcome these drawbacks. Paraffin wax and soya wax were used as PCMs and multi-walled carbon nanotubes and graphene oxide were used as nano-additives. High-Density Polyethylene (HDPE) is used as a supporting matrix. Leakage test suggest maximum loading of 40 wt% and 35 wt% of paraffin wax and soya wax in HDPE without any leakage at elevated temperature. The prepared SSCPCM shows substantially better thermal energy storage capacity along with improved thermal conductivity. A maximum rise of 260.8% in thermal conductivity was observed in paraffin wax supported by HDPE and loaded with 3 wt% of multi-walled carbon nanotube nanoparticles. The heating and cooling performance suggests an improvement in the heating and cooling rate by adding nano-additives. The prepared SSCPCM are also thermally stable at elevated temperatures up to 150 °C.
Evaluation of Lateral Sealing of Faults Based on Porosity: A Case Study of the F1 Fault of the Nanpu No. 5 Structure in the Nanpu Sag
Authors: Zhang Yuwei , Yu Yinghua , Zhang Yaxiong , Yuan Hongqi
Published: May 2024

The lateral sealing of a fault plays a pivotal role in the efficacy of a fault trap and its degree of hydrocarbon filling. Nevertheless, the evaluation of this phenomenon remains a challenging task, with evaluation methods either unable to accurately reflect subsurface reality or obtaining the necessary parameters difficult. In light of these considerations, a porosity-based fault laterality evaluation method was proposed, with the F1 Fault of the Nanpu No. 5 structure in the Nanpu Sag serving as the research object. First, the relationship between porosity and the product of burial depth and shale content was established using measured porosity, burial depth, and shale content data of the surrounding rocks in the study area. Subsequently, the reservoir rock porosity was obtained by employing logging data or core samples or by calculating the reservoir rock shale content from natural gamma logging data. Concurrently, the shale content of fault rock was calculated using three-dimensional (3D) seismic data, mud logging data, and natural gamma logging data, thereby enabling its porosity to be determined. Finally, the porosity difference between the two was employed to assess the lateral closure of faults. The results indicate that the porosity difference is less than 0 at lines L1~L3 of the F1 Fault, which suggests that the fault is not laterally closed at this site. Conversely, the F1 Fault is laterally sealed at this location, as indicated by the porosity difference being greater than 0 at lines L4~L10. The findings of this evaluation were found to be in close alignment with the actual distribution of oil and water, indicating that the proposed method can accurately evaluate the lateral closure of faults with developed fault rocks and provide valuable guidance for the exploration of faulted oil and gas reservoirs.
A Zonal Approach for Wide-Area Temporary Voltage Quality Assessment in a Smart Grid
Authors: Forcan Miodrag , Simović Aleksandar , Jokić Srđan , Forcan Jovana
Published: May 2024

Wide-area voltage quality assessment represents one of the mandatory objectives for distribution system operators in the development of advanced distribution management systems supporting smart grid requirements. This paper introduces a zonal approach for wide-area temporary voltage quality evaluation in a distribution network. The concept of temporary voltage quality evaluation and assessment is recommended to incentivize active/online management of voltage quality issues. A decision support system based on simple deterministic rules is proposed for rating the voltage quality zones in a distribution network and making recommendations to the distribution system operator. Voltage RMS level, unbalance, and total harmonic distortion are considered voltage quality indices representing the inputs in the decision support system. Residential, commercial, and industrial load types are considered when setting the thresholds for voltage quality indices. The proposed zonal approach for the division of distribution networks in voltage quality zones is applied to the example of a typical European-type distribution network. The operation of a decision support system is tested using the developed distribution smart grid model. The following simulation case studies are conducted: loads with low power factors, manual voltage regulation at MV/LV transformers, unbalanced loads, integration of solar power plant, and nonlinear loads. The obtained simulation results reveal the benefits of the proposed voltage quality assessment approach. Cybersecurity challenges that may impact the proposed approach are addressed, including security vulnerabilities, data privacy, and resilience to cyber threats.
FCS-MPC Based on Dimension Unification Cost Function
Authors: Han Jinyang , Yuan Hao , Li Weichao , Zhou Liang , Deng Chen , Yan Ming
Published: May 2024

Finite Control Set Model Predictive Control (FCS-MPC) has the ability to achieve multi-objective optimization, but there are still many challenges. The key to realizing multi-objective optimization in FCS-MPC lies in the design of the cost function. However, the different dimensions of penalty terms in the cost function often lead to difficulties in designing weighting coefficients. Incorrect weighting coefficients may result in truncation errors in calculations of DSPs and FPGAs, thereby affecting the algorithm’s control performance. Therefore, this article focuses on a system driving an induction motor with a three-level Neutral Point Clamped (NPC) inverter, and selects stator current and switching frequency as penalty terms in the cost function. An improved method is proposed to unify the dimensions of both penalty terms in the cost function. By unifying the dimensions of the penalty terms, a simple design of weighting coefficients can be achieved. Subsequently, to balance the inverter’s switching frequency and the dynamic response performance of the motor, a composite cost function is further proposed. Finally, the rationality of the proposed method is validated through simulation and experimental platforms.
Numerical Study on Steam Cooling Characteristics in a Isosceles Trapezoidal Channel with Pin-Fin Arrays at Turbine Blade Trailing Edge
Authors: Xi Lei , Gao Yuan , Ruan Qicheng , Gao Jianmin , Xu Liang , Li Yunlong
Published: May 2024

Using the SST k-ω turbulence model, a comprehensive numerical investigation was conducted to analyze the flow and heat transfer characteristics of steam within an isosceles trapezoidal cooling channel with pin-fin arrays modeled from the trailing edge of a F-class gas turbine high-temperature blade. The influence laws of various parameters, including the Reynolds number (Re, from 10,000 to 50,000), dimensionless pin-fin diameter (d/H, from 0.4 to 0.8), and dimensionless pin-fin spacing (S/H, from 1.6 to 2.4), on the flow and heat transfer performance of the isosceles trapezoidal cooling channel with pin-fin arrays were examined. Sensitivity analysis was employed to determine the relative significance of these influence parameters on the cooling performance of the isosceles trapezoidal channel with pin-fin arrays. Finally, the corresponding heat transfer and friction correlations within the investigated parameter range were developed. The research findings reveal that under different Reynolds numbers, as the dimensionless pin-fin diameter increases from 0.4 to 0.8, the friction factor within the isosceles trapezoidal cooling channel with pin-fin arrays increases by a factor of 3.25 to 3.41, while the overall average Nusselt number improves by 31.05% to 37.41%. Conversely, when the dimensionless pin-fin spacing increases from 1.6 to 2.4, the friction factor within the isosceles trapezoidal cooling channel with pin-fin arrays decreases by 67.38% to 69.18%, accompanied by a reduction in the overall average Nusselt number by 24.95% to 31.14%. When both the flow performance and heat transfer performance are taken into account, the importance of the influence parameters ranks as follows: Reynolds number, pin-fin diameter, and pin-fin spacing. It also suggests that smaller pin-fin diameters and larger pin-fin spacing should be selected in the design stage based on the variation laws of integrated thermal-hydraulic performance. The results may provide valuable references and insights for the design of steam cooling structures within high-temperature turbine blade trailing edge channels in advanced gas turbines.
Online EVs Vehicle-to-Grid Scheduling Coordinated with Multi-Energy Microgrids: A Deep Reinforcement Learning-Based Approach
Authors: Pan Weiqi , Yu Xiaorong , Guo Zishan , Qian Tao , Li Yang
Published: May 2024

The integration of electric vehicles (EVs) into vehicle-to-grid (V2G) scheduling offers a promising opportunity to enhance the profitability of multi-energy microgrid operators (MMOs). MMOs aim to maximize their total profits by coordinating V2G scheduling and multi-energy flexible loads of end-users while adhering to operational constraints. However, scheduling V2G strategies online poses challenges due to uncertainties such as electricity prices and EV arrival/departure patterns. To address this, we propose an online V2G scheduling framework based on deep reinforcement learning (DRL) to optimize EV battery utilization in microgrids with different energy sources. Firstly, our approach proposes an online scheduling model that integrates the management of V2G and multi-energy flexible demands, modeled as a Markov Decision Process (MDP) with an unknown transition. Secondly, a DRL-based Soft Actor-Critic (SAC) algorithm is utilized to efficiently train neural networks and dynamically schedule EV charging and discharging activities in response to real-time grid conditions and energy demand patterns. Extensive simulations are conducted in case studies to testify to the effectiveness of our proposed approach. The overall results validate the efficacy of the DRL-based online V2G scheduling framework, highlighting its potential to drive profitability and sustainability in multi-energy microgrid operations.
Modeling and Prediction of Carbon Monoxide during the Start-Up in ICE through VARX Regression
Authors: Garcia-Basurto Alejandro , Perez-Cruz Angel , Dominguez-Gonzalez Aurelio , Saucedo-Dorantes Juan J.
Published: May 2024

In a global society that is increasingly interrelated and focused on mobility, carbon monoxide emissions derived from internal combustion vehicles remain the most important factor that must be addressed to improve environmental quality. Certainly, air pollution generated by internal combustion engines threatens human health and the well-being of the planet. In this regard, this paper aims to address the urgent need to understand and face the CO emissions produced by internal combustion vehicles; therefore, this work proposes a mathematical model based on Auto-Regressive Exogenous that predicts the CO percentages produced by an internal combustion engine during its start-up. The main goal is to establish a strategy for diagnosing excessive CO emissions caused by changes in the engine temperature. The proposed CO emissions modeling is evaluated under a real dataset obtained from experiments, and the obtained results make the proposed method suitable for being implemented as a novel diagnosis tool in automotive maintenance programs.
Resveratrol Effects on Metabolic Syndrome Features: A Systematic Review and Meta-Analysis
Authors: Batista-Jorge Gislaine C. , Barcala-Jorge Antônio S. , Lelis Deborah F. , Santos Daniel E. , Jorge Antônio H. , Monteiro-Junior Renato S. , Santos Sérgio H. S.
Published: May 2024

Resveratrol is a natural polyphenol with important anti-inflammatory and antioxidant properties for treating cardiometabolic disorders. Therefore, the present meta-analysis aimed to review and investigate the oral resveratrol supplementation effects on metabolic syndrome (MetS) components. The bibliographic search was carried out in 2023 in the following databases: PubMed, Web of Science, and Scopus. Studies that investigated the oral resveratrol effects on the MetS parameters were included. Statistical analyses were performed using RevMan Software V.5.3. The main findings showed that resveratrol significantly decreased systolic and diastolic blood pressure while having no significant effects on waist circumference and high-density lipoprotein levels. In addition, glucose level was significantly decreased in the subgroup of studies reporting change from baseline means, although the overall effect was not statistically significant (p = 0.81), while triglyceride levels were increased after the treatment period. In conclusion, the present meta-analysis evidenced the potential therapeutic effect of resveratrol on improving some MetS features, especially regarding systolic blood pressure, diastolic blood pressure, and glucose reduction; however, the results are still borderline and sometimes controversial, which might be justified by the methodological and statistical heterogeneity of the studies, with the latter varying from 17 to 57%.
Forecasting Daily Activity Plans of a Synthetic Population in an Upcoming District
Authors: Belaroussi Rachid , Delhoum Younes
Published: May 2024

The modeling and simulation of societies requires identifying the spatio-temporal patterns of people’s activities. In urban areas, it is key to effective urban planning; it can be used in real estate projects to predict their future impacts on behavior in surrounding accessible areas. The work presented here aims at developing a method for making it possible to model the potential visits of the various equipment and public spaces of a district under construction by mobilizing data from census at the regional level and the layout of shops and activities as defined by the real estate project. This agent-based model takes into account the flow of external visitors, estimated realistically based on the pre-occupancy movements in the surrounding cities. To perform this evaluation, we implemented a multi-agent-based simulation model (MATSim) at the regional scale and at the scale of the future district. In its design, the district is physically open to the outside and will offer services that will be of interest to other residents or users of the surrounding area. To know the effect of this opening on a potential transit of visitors in the district, as well as the places of interest for the inhabitants, it is necessary to predict the flows of micro-trips within the district once it is built. We propose an attraction model to estimate the daily activities and trips of the future residents based on the attractiveness of the facilities and the urbanistic potential of the blocks. This transportation model is articulated in conjunction with the regional model in order to establish the flow of outgoing and incoming visitors. The impacts of the future district on the mobility of its surrounding area is deduced by implementing a simulation in the projection situation.
Clinical Significance of the Plasma Biomarker Panels in Amyloid-Negative and Tau PET-Positive Amnestic Patients: Comparisons with Alzheimer’s Disease and Unimpaired Cognitive Controls
Authors: Chang Hsin-I , Huang Kuo-Lun , Huang Chung-Gue , Huang Chi-Wei , Huang Shu-Hua , Lin Kun-Ju , Chang Chiung-Chih
Published: May 2024

The purpose of this study was to investigate whether plasma biomarkers can help to diagnose, differentiate from Alzheimer disease (AD), and stage cognitive performance in patients with positron emission tomography (PET)-confirmed primary age-related tauopathy, termed tau-first cognitive proteinopathy (TCP) in this study. In this multi-center study, we enrolled 285 subjects with young-onset AD (YOAD; n = 55), late-onset AD (LOAD; n = 96), TCP (n = 44), and cognitively unimpaired controls (CTL; n = 90) and analyzed plasma Aβ42/Aβ40, pTau181, neurofilament light (NFL), and total-tau using single-molecule assays. Amyloid and tau centiloids reflected pathological burden, and hippocampal volume reflected structural integrity. Receiver operating characteristic curves and areas under the curves (AUCs) were used to determine the diagnostic accuracy of plasma biomarkers compared to hippocampal volume and amyloid and tau centiloids. The Mini-Mental State Examination score (MMSE) served as the major cognitive outcome. Logistic stepwise regression was used to assess the overall diagnostic accuracy, combining fluid and structural biomarkers and a stepwise linear regression model for the significant variables for MMSE. For TCP, tau centiloid reached the highest AUC for diagnosis (0.79), while pTau181 could differentiate TCP from YOAD (accuracy 0.775) and LOAD (accuracy 0.806). NFL reflected the clinical dementia rating in TCP, while pTau181 (rho = 0.3487, p = 0.03) and Aβ42/Aβ40 (rho = −0.36, p = 0.02) were significantly correlated with tau centiloid. Hippocampal volume (unstandardized β = 4.99, p = 0.01) outperformed all of the fluid biomarkers in predicting MMSE scores in the TCP group. Our results support the superiority of tau PET to diagnose TCP, pTau181 to differentiate TCP from YOAD or LOAD, and NFL for functional staging.