bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influencing Factors of Breakdown Pressure in the Mahu Conglomerate Reservoir under Perforation Conditions
Authors: Jia Wenting , Mou Jianye , Li Xiaowei , Wang Xinliang , Zhang Shicheng , Wang Lifeng , Xu Yajun 
Published: May 2024

Abstract
The Mahu Oilfield in Xinjiang, China, is the world’s largest conglomerate oilfield with massive geological reserves. In the multi-cluster staged of horizontal well fracturing, the breakdown pressure is high, and the fracture is difficult to initiate. Therefore, lowering the breakdown pressure is the key to hydraulic fracturing safely and efficiently. In this paper, we first develop a new water jetting experimental apparatus that can adjust perforation parameters to simulate spiral perforation in the oil field. It consists of perforation angle, position, and depth. The researchers went to the Mahu area for geological investigation and excavated conglomerate outcrops from the Baikouquan formation to conduct true triaxial hydraulic fracturing physical simulation experiments. The research results indicate that water jetting perforation can reduce the breakdown pressure by 6 MPa under immutable in-situ stress magnitude and distribution. It is easier to initiate when the angle between the perforation tunnel and the maximum horizontal principal stress is 0°, with the lowest breakdown pressure. If natural fractures are developed near the perforation hole, the communication between the perforation tunnel and the natural fractures prominently reduces the difficulty of fracture initiation. After fracturing, it is easy to form complex multi-fractures with high tortuosity and surface roughness, and the breakdown pressure declines sharply. The research results provide theoretical support for reducing the breakdown pressure in conglomerate reservoirs with strong heterogeneity.
Estimating the carbon footprint of post-flood urban road network restoration efforts: A case study in Carlisle
Authors: Zhong Weichen , Howard Guy , Neal Jeffrey 
Published: May 2024

Abstract

Climate change and urbanization are increasing the risk of flood disasters in vulnerable areas. Urban road infrastructure can be affected by floods, and subsequent restoration creates an additional carbon emission burden. These emissions are likely to compromise local decarbonization efforts, but there remains a lack of tools for quantifying the environmental impact of reconstruction projects after disasters. This study aims to develop an assessment framework to reveal the carbon footprint of post-flood road network restoration projects. An interdisciplinary model was developed, integrating knowledge in hydrology, civil engineering, and environmental science. This paper presents scenario simulations with the maximum flood depth (MFD) ranging from 0.1 m to 5.0 m and a case study in Carlisle, UK. Results show that floods with MFD over 0.5 m had significant impacts on pavements. The resilience to floods on low-volume roads was weaker, but the restoration emission intensity of main roads was significantly higher. From the perspective of an urban case, after a 70-hour flood event with an average MFD of 0.9 m, the total carbon footprint of road network restoration was 73.89 tCO2e, offsetting about 0.49% of local carbon reduction efforts for the month. Specifically, emissions from restoring low-volume roads accounted for 58.64%. Indirect carbon emissions from material production (approx. 66%) and delivery (approx. 30%) were much higher than direct emissions from onsite tasks (approx. 4%). Measures such as material improvement, delivery optimization, and construction material reuse can help mitigate the emission burden of restoration projects. A major uncertainty in the computation was ignoring the differences induced by the climatic context, but addressing this limitation would require support from pavement damage experts. This study provides quantitative tools for understanding infrastructure-related environmental impacts caused by flood disasters. The assessment framework proposed in this work is also expected to be applied to wider spatial-temporal scenarios to enrich decision-making references.
Topology Optimization of Thermal Initial Value Problems Exploiting Efficient Harmonic Analysis
Authors: Işıklar Göktuğ , Christiansen Rasmus Ellebæk , Sigmund Ole 
Published: May 2024

Abstract

Topology optimization can be employed to manipulate transient thermal behavior for heat transfer devices. As a gradient-based approach, transient topology optimization faces challenges with the CPU cost of the associated forward and backward time-stepping procedure. This study introduces a harmonic analysis-based substitute optimization method to alleviate these computational challenges. Using an analytical solution for a one-dimensional heat conduction problem, we derive a conversion coefficient linking harmonic excitation frequency to the desired transient time instance. Applying this harmonic formulation in the topology optimization of a two-dimensional transient heat conduction problem shows a remarkable speedup, around a factor of 20 per design iteration, with less than a 5% decrease (at most) in the figure of merit compared to the transient approach. Extending the study to include heat convection displays a stable region where the proposed harmonic substitute method sustains the same computational efficiency with less than a 10% difference for objective value comparison in the worst-case scenario.
Biology and Management of Tea Mosquito Bug, Helopeltis Antonii on Neem
Authors: Chaitanya B , Bheemanna M , Prabhuraj Aralimarad , Murthy M Shankara , Harischandra Naik R , Aswathanarayana D S 
Published: May 2024

Abstract

A study was conducted to evaluate the bio-efficacy of entomopathogens and synthetic insecticides for the management of tea mosquito bug, Helopeltis antonii on neem as well to study its biology and morphometrics. It was found that the life cycle of H. antonii, unfolds over 37 to 48 days when hosted on neem, encompassing an incubation period of 7.45 ± 1.19 days and a nymphal phase lasting 16.05 ± 1.28 days. The male members exhibit a longevity of 17.85 ± 1.63 days, while the females live slightly longer at 19.2 ± 1.88 days. Hatching percentages range from 62.5% to 86.67%, with adult emergence rates falling between 83.33% and 92.85%. Notably, the population skews towards males, maintaining a sex ratio of 1:1.22.In insecticide testsfor managing the tea mosquito bug on neem, lambda-cyhalothrin and thiamethoxam on neem show high efficacy, while Lecanicillium lecanii has the least impact.
Longitudinal monitoring of sewershed resistomes in socioeconomically diverse urban neighbourhoods
Authors: Parkins Michael , Lee Jangwoo , Xiang Kevin , Au Emily , Sarabi Shahrzad , Acosta Nicole , Bhatnagar Srijak , Doorn Jennifer Van , Bertazzon Stefania , Conly John , Rennert-May Elissa , Pitout Johann , Lee Bonita , Pang Xiaoli , O'Grady Christine , Frankowski Kevin , Hubert Casey 
Published: May 2024

Abstract

Understanding factors associated with antimicrobial resistance (AMR) distribution across populations is a necessary step in planning optimal mitigation measures. While associations between AMR and socioeconomic-status (SES), including factors like income, employment, education, have been increasingly recognized in low- and middle-income settings, this interplay is less clear in high-income countries. We explored the relationship between SES and AMR in Calgary, Canada using spatially-resolved wastewater-based surveillance of resistomes detected by metagenomics across socio-economically diverse urban neighbourhoods. Conducting this comparison during the height of COVID-related international travel restrictions (Dec.2020-Oct.2021) allowed the hypotheses linking SES and AMR to be assessed with limited confounding. Wastewater metagenomes from eight diverse neighbourhoods exhibited highly similar resistomes, with no quantitative differences (p > 0.05), low Bray-Curtis dissimilarity, and no significant correlations with SES. By comparison, dissimilarity was observed between globally-sourced resistomes from 244 cities (p < 0.05), underscoring the homogeneity of resistomes in Calgary’s sub-populations. The analysis of globally-sourced resistomes alongside Calgary resistome further revealed lower AMR burden in Calgary relative to other cities around the world was particularly pronounced for some of the most clinically-relevant AMR genes (e.g., beta-lactamases, macrolide-lincosamide-streptogramin). This work showcases the effectiveness of inclusive and comprehensive wastewater-based surveillance for exploring the interplay between SES and AMR.
Clinical Trauma Severity of Indoor and Outdoor Injurious Falls Requiring Emergency Medical Service Response
Authors: Burford Kathryn G. , Itzkowitz Nicole G. , Crowe Remle P. , Wang Henry E. , Lo Alexander X. , Rundle Andrew G. 
Published: May 2024

Abstract

Background: Injurious falls represent a significant public health burden. Research and polices have primarily focused on falls occurring indoors despite evidence that outdoor falls account for 47-58% of all falls requiring some medical attention. This study compared the clinical trauma severity of indoor versus outdoor injurious falls requiring Emergency Medical Services (EMS) response.
Methods: Using the 2019 National Emergency Medical Services Information System (NEMSIS) dataset, we identified the location of patients injured from falls that required EMS response. We classified injury severity using 1) the Revised Trauma Score for Triage (T-RTS): ≤ 11 indicated the need for transport to a Trauma Center; 2) Glasgow Coma Scale (GCS): ≤8 and 9–12 indicated moderate and severe neurologic injury; and 3) patient clinical acuity by EMS: Dead, Critical, Emergent, Low.
Results: Of 1,854,909 encounters for patients with injurious falls, the vast majority occurred indoors (n=1,596,860) compared to outdoors (n=152,994). The proportions of patients with moderate or severe GCS scores, were comparable between those with indoor falls (3.0%) and with outdoor falls on streets or sidewalks (3.8%), T-RTS scores indicating need for transport to a Trauma Center (5.2% vs 5.9%) and EMS acuity rated as Emergent or Critical (27.7% vs 27.1%).Injurious falls were more severe among male patients compared to females: and males injured by falling on streets or sidewalks had higher percentages for moderate or severe GCS scores (4.8% vs 3.6%) and T-RTS scores indicating the need for transport to a Trauma Center (7.3% vs 6.5%) compared to indoor falls. Young and middle-aged patients whose injurious falls occurred on streets or sidewalks were more likely to have a T-RTS score indicating the need for Trauma Center care compared to indoor falls among this subgroup. Yet older patients injured by falling indoors were more likely to have a T-RTS score indicating the need for Trauma Center than older patients who fell on streets or sidewalks.
Conclusions: There was a similar proportion of patients with severe injurious falls that occurred indoors and on streets or sidewalks. These findings suggest the need to determine outdoor environmental risks for outdoor falls to support location-specific interventions.
Utilization of agrowaste for arsenic biosorption: enhancing efficacy and assessing the suitability of plant and animal growth in post-adsorbed solution
Authors: Ghosh Malaya , Dey Pubali , Mandal Abhijit , Giri Sarbani 
Published: May 2024

Abstract

Arsenic is known to have detrimental effects on living bodies when exposed to contaminated groundwater. Therefore, a cost-effective way to eliminate arsenic from aquatic sources is essential. Our study evaluated the efficacy of eight different types of easily accessible agricultural waste for arsenic removal. The safety assessment of the post-adsorbed solution in plant and animal test models such as Allium cepa and Daphnia magna was also evaluated. The results showed that the efficiency of the adsorbents depends on the type of agricultural waste utilized. In the case of citrus agrowastes, maximum adsorption (94–95%) was attained at lowest 15 min contact time indicating very rapid saturation of adsorption sites and for other adsorbents, with increase of contact time there was gradual increase in adsorption of arsenic. Allium cepa toxicity test showed that arsenic-exposure caused significant decrease in root length (2.80 ± 0.89 cm) and reduction in mitotic index (6.31 ± 1.79%) that can be reverted to normal after the roots were grown in post-adsorbed medium. Similarly, solutions treated with different agricultural wastes except citrus bioadsorbents showed significantly higher survival rates and litter sizes of Daphnia magna post biosorption. Agricultural waste with citric characteristics removed arsenic more effectively than other chosen agricultural wastes but the solution generated by adsorption with citric agrowaste does not support plant and animal growth. Among the other chosen adsorbents, rice husk has been found to be highly suitable for plant and animal growth by reducing the toxic effects of arsenic.
Evaluation of Drain Quality and Nutrient Loads Management Scenarios by Using QUAL2kw Model
Authors: Abyaz Seyedeh Razieh Shabestani , Samani Jamal Mohammadvali , Navabian Maryam 
Published: May 2024

Abstract

The examination of wastewater and effluents flowing into receiving water bodies is crucial for identifying pollutant sources and implementing scenarios to reduce them. In this study, QUAL2kw was used to identify, assess, and predict the pollutant load of a drainage canal located 6 kilometers away from Anzali Wetland. Initially, the model was calibrated and validated with data collected in 2017. The NRMSE of the values was mostly less than 20%, except for flow accounting for 37% during calibration. The model did well in simulating EC and ammonium levels, but there is room for improvement in predicting nitrate and inorganic P concentrations. Field visits and sampling were done during the rice growth period in April-June 2021. The model was simulated for a three-time series in 2021, simulation showed that the month of May was the most critical, as the levels of nitrates, ammonium, and phosphates were at their highest. Then scenarios were considered to reduce nutrient loads. Reducing the amount of fertilizer led to a 9–27% while applying water stress resulted in a 0.1-1% reduction in the discharge outflow from the drain and less than 1% reduction in the amount of ammonium and nitrate. It is concluded that reduction in fertilization is more efficient in reducing concentrations and pollutant loads at the exit point of the canal to water resources compared to applying water stress since urea fertilizer contains a high percentage of nitrogen and declining water application can enhance the soil’s nutrient retention ability but only to a small degree.
SCWIR: A rumor propagation model considering user waiting behavior
Authors: Wu Hai , Yan Xin , Wang Hongbin , Gao Shengxiang , Deng Zhongying 
Published: May 2024

Abstract

The rapid development of the Internet has brought convenience to people in accessing information, but it has also exacerbated the spread of rumors. Therefore, it becomes crucial to study the propagation patterns of rumors and devise corresponding suppression strategies. In the study of rumor propagation, the existing rumor propagation model studies have not fully considered the neutral wait-and-see population, nor have they taken into account the possibility of users waking up midway after believing in the rumor to wait and see for a second time. To address the above shortcomings, this paper established the SCWIR (Susceptible, Commented, Waited, Infected, Recovered) rumor propagation model, which introduced the Commenter (Commented, C) and the Waited (Waited, W) to better model users' positions of commenting and neutral waiting in rumor events. Based on the proposed model, this paper investigated the transformation process of five types of users, namely susceptible users, commenters, waiting users, spreaders, and recovery users, under the influence of government intervention, higher education coverage rate, and information timeliness; and conducted simulation experiments to verify the validity of the proposed model. The research results show that the model proposed in this paper can better reflect the possible behaviors of users such as commenting on rumors, neutral waiting, and spreading rumors during the rumor-spreading process. It achieves good performance in predicting the peak periods of rumor outbreaks, the peak value of outbreaks, the lifecycle of rumors, and the changing proportions of various members over time.
Effect of Al and AP particle sizes on the condensed combustion products characteristics of aluminized NEPE propellants
Authors: Tu Chengyin 
Published: May 2024

Abstract

Aluminum (Al) is usually added to solid propellants to improve the combustion performance, however the condensed combustion products (CCPs) especially the large agglomerates generated from aluminum combustion can reduce the specific impulse of the engine, and result in two-phase loss, residue accumulation and throat liner ablation. Al and AP, as important components of NEPE propellants, can affect the formation process of the CCPs of aluminized NEPE propellants. To clarify the effect of Al and AP particle sizes on the properties of the CCPs of aluminized NEPE propellants, a constant-pressure quench vessel was adopted to collect the combustion products of four different formulations of NEPE propellants. It was found that the condensed combustion products are mainly divided into aluminum agglomerates and oxide particles, the diameter of the aluminum agglomerates of these four different formulations of NEPE propellants at 7MPa was smaller than that in 3MPa, and the shells of the aluminum agglomerates were smoother and the spherical shape was more perfect. X-ray diffraction analysis of the CCPs of the four NEPE propellants under 3MPa revealed the presence of both Al and Al2O3. With the increase of the particle size of Al and AP, the oxidation degree of aluminum particles decreases. The particle size of the CCPs of the four different formulations of NEPE propellants under 1MPa and 3MPa was analyzed by using a laser particle size analyzer, it is found that the increase of AP particle size is helpful to reduce the size of condensate combustion products. Based on the classical pocket theory, establishing a new agglomeration size prediction model, which can be used to predict the agglomeration size on the burning surface. Compared with the empirical model, the new agglomeration size prediction model is in good agreement with the experimental results.
Mix Design of Sprayed Steel Fiber Recycled Concrete
Authors: Pan Xiangguang , Sun Jilin , Quan Xianzheng , Si Jiaxiao , Sun Sibo , Sun Xuran , Liu Chuanqi 
Published: May 2024

Abstract

Sprayed steel fiber recycled concrete (SSFRC) is a new type of green composite building material. This study examines the impact of water-cement ratio, recycled aggregate (RA) replacement rate, and steel fiber (SF) volume ratio on concrete properties such as slump, compressive strength, and bending strength. To accomplish this, 9 orthogonal experimental designs with 3 factors and 3 levels are utilized. The primary and secondary order of factors affecting the slump, compressive strength, and bending strength of fresh concrete are obtained by analyzing experimental data. To calculate the mix ratio, the mathematical model is obtained by controlling single factor variables and fitting relationships of relevant factor data based on the analysis results of the significance of orthogonal experiments. By investigating the replacement rates of 0%, 50%, and 100% RA, we examined the ideal sand content for SSFRC. The slump values of 24 mix ratio tests were analyzed, leading to the identification of the optimal outcomes associated with sand content percentages of 49%, 51%, and 53%. Finally, we obtained the calculation method for the mix ratio of SSFRC. Based on the example calculation and verification presented in this article, it can be concluded that the mix design method proposed for SSFRC is accurate, simple, convenient, and practical.
Intelligent Agents in Educational Institutions: AEdBOT– A Chatbot for Administrative Assistance using Deep Learning Hybrid Model Approach
Authors: Ali Muhammad Shahroze , Anwar Muhammad Waseem , Azam Farooque , Ashraf Muhammad Hashir 
Published: May 2024

Abstract

Chatbots substantially improve administrative support for educational institu- tions facing immense pressure during admissions. Chatbots not only automate repetitive tasks, handle large volumes of inquiries, collecting data from inter- actions but also provide an additional way for students to access information. Existing chatbots are built on traditional Artificial Intelligence (AI) approaches where the accuracy required for seamless real-time interactions is usually compro- mised. This article presents novel AEdBOT - an AI-based Educational ChatBOT system where a novel Deep Learning (DL)-based Hybrid model approach is proposed grounded on integrating informational retrieval and generative neural networks. Moreover, a novel Natural Language Processing (NLP) pipeline is developed on top of the open-source Rasa platform to aid with BERT (Bidi- rectional Encoder Representation Transformer) for dense feature extraction and DIET (Dual Intent and Entity Transformer) Classifier for intent classification and entity extraction from the natural language text. Furthermore, the customized dual fallback classifier algorithm is developed to provide the self-learning ability to
a chatbot on out-of-scope inputs and acts as a recommendation system. The effec- tiveness of the proposed chatbot is established through two real-life datasets from educational institutes. For the first dataset, AEdBOT achieved 94.7%, 96.0%, 96.0%, and 95.1% precision, accuracy, recall, and F1-Score, respectively at an average mean response time of 216.43ms per query and a user-friendliness score of 77.5 on the System Usability Scale (SUS). The second dataset is used from the literature for comparative analysis, and AEdBOT attained 76.2%, 83.7%, 77.7%, and 79.1% accuracy, precision, F1-Score, and recall, respectively. Experiment results reveal that AEdBOT significantly improves response accuracy and outperforms state-of-the-art educational chatbots.