bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global Probabilistic Forecasting for Multiple Tight Gas Wells Using Deep Autoregressive Networks
Authors: Han Jiangxia , Xue Liang , Liu Qianjun , Wei Yunsheng , Chen Haiyang , Dong Yubing , Liu Yuetian , Qi Yadong , Wang Junlei 
Published: September 2024

SummaryTraditional methods for forecasting production rate, such as Arps, analytical techniques, and recurrent neural network (RNN)–based deep learning, are mainly point prediction techniques developed within the framework of single-well forecasting. These methods often face limitations stemming from single-well historical production data and model assumptions, hindering their ability to consider the influence of development patterns of other production wells within the block on the target well. In addition, they struggle to predict the multiple production rate time series simultaneously and often fail to quantify uncertainty in predictions or adequately exploit extensive relevant historical production data. To tackle these challenges, we propose a model based on the deep autoregressive recurrent neural network (DeepAR), leveraging related multiwell production rate data to enable global modeling and probabilistic forecasting. This model incorporates dynamic covariate and static categorical variable data, integrating Bayesian inference and using gradient descent algorithms and maximum likelihood estimation methods to derive a comprehensive historical-future production probability evolution pattern shared across multiple wells. Leveraging data from 943 tight gas wells, a comprehensive evaluation of the DeepAR model’s performance was undertaken, encompassing the comparison of prediction accuracy with long short-term memory (LSTM), classification prediction, cold-start prediction, and single-well multitarget prediction scenarios, summarizing the applicability conditions for each. The research findings highlight that DeepAR integrates the acquired comprehensive production probability evolution pattern with specific production historical data of the target well to formulate a “comprehensive + specific” production probability prediction approach, resulting in improved stability and accuracy. On average, DeepAR demonstrates a 58.79% reduction in normalized deviation (ND) compared to the LSTM model, showcasing enhanced stability, particularly in scenarios involving frequent well shut-ins and openings. Moreover, DeepAR can learn static categorical features, with the classification model resulting in a 27.15% reduction in the ND compared to the unclassified model. Furthermore, DeepAR adeptly addresses the challenge of limited data availability, achieving cold-start prediction and facilitating multitarget single-well training and prediction while considering the interdependency among multiple variables over time and effectively mitigating the issue of missing auxiliary variables during the prediction phase. This study contributes to a broader understanding of production forecasting and analysis of production dynamics methods from a big data perspective.
Visiting behaviour of Moringa oleifera flowers by potential insect pollinators
Authors: BAZIE Babou Frédéric 
Published: September 2024

Abstract

The influence of potential insect pollinators is decisive in the fruiting process of many cross-pollinated plants. The aim of this study was to determine the behaviour of potential pollinating insects visiting Moringa oleifera flowers. Collections were carried out from July to September 2018 and 2019, followed by monitoring of the behavior of potential insect pollinators from July to September 2020 in the Sahelian, North Sudanian and South Sudanian zones. The methodology consisted in the use of a Fauchoir net for the exhaustive collection of insects visiting Moringa. The results revealed that a total of 50 species of pollinating insects divided into 25 families and three orders (Hymenoptera, Diptera and Lepidoptera) were identified on the basis of the presence of body hairs on Moringa. Of these, nine insect species collect both nectar and pollen. These are : Xylocopa violacea (L.), Anthophora plumipes (Pallas, 1772), Apis mellifera (L.), Xylocopa pubescens (Spinola, 1838), Pollenia rudis (F.), Alophora hemiptera (F.), Syrphus ribesii (L.), Danaus chrysippus (L.) and Pieris rapae (L.). The times of day when pollinating insects appear on Moringa flowers vary from species to species. The abundance of these pollinators and the duration of their presence on the flowers vary according to geographical area and pollinator species. Hymenoptera are the dominant pollinators in Moringa plantations.
Investigation of Kinetics, Reaction Mechanisms, Thermodynamics, and Synergetic Effects in Co-Pyrolysis of Wood Sawdust and Linear Low-Density Polyethylene using the Thermogravimetric Approach
Authors: Dhibar Nayan Chand , Busigari Rajasekhar Reddy , Patel Madhumita 
Published: September 2024

Abstract

This study focused on investigating thermal degradation behaviors, kinetics, reaction mechanisms, synergistic effects, and thermodynamic parameters of wood sawdust (WSD), linear low-density polyethylene (LLDPE), and their blends (LW1:3, LW1:1, and LW3:1) during co-pyrolysis in a thermogravimetric analyzer (TGA). Thermal behavior exhibited a LW1:3 blend (25 wt.% LLDPE) showing significant mass loss at lower temperatures (150 to 300°C) compared to the individual feedstocks, such as 150 to 400°C and 300 to 520°C for WSD and LLDPE, respectively. The iso-conversional methods (KAS, FWO, and FM) were used to determine the kinetic parameters (Ea and A), and the activation energy drop was highest for the LW1:3 blend. According to the master plots, the third-order reaction (O3), nucleation (P2/3), and diffusional model (D4) were the predominant reaction mechanisms for the co-pyrolysis of the LW1:3, LW1:1, and LW3:1 blend, respectively. The thermodynamic parameters demonstrate that a small amount of plastic addition into WSD can improve the reactivity of the blend, shorten the reaction time, and cause less energy-intensive reactions. The values of ΔH, ΔG, and ΔS also confirmed the co-pyrolysis process’s spontaneity and endothermic nature. The Fourier transforms infrared spectrometer (FTIR) spectra of raw feedstock, blends, and their biochar revealed some of the peaks were shifted, the intensity was reduced, and disappearance can happen when the temperature was increased. Using the experimental and theoretical/predicted activation energies, the parity chart illustrates the synergistic effects of co-pyrolysis of different blends, and the LW1:3 blend has a favorable synergistic impact. These results could be helpful in process optimization and designing an effective reactor system for co-pyrolysis.
Generation of phenotypically stable and functionally mature human bone marrow MSCs derived Schwann cells via the induction of human iPSCs-derived sensory neurons
Authors: Pan Yu , Lin Haohui , Chung Manhon , Yang Yi , Zhang Li , PAN Xiaohua , Cai Sa 
Published: September 2024

Abstract

Background
Phenotypically unstable Schwann cell-like cells (SCLCs), derived from mesenchymal stem cells (MSCs) require intercellular contact-mediated cues for Schwann cell (SCs)-fate commitment. Although rat dorsal root ganglion (DRG) neurons provide contact-mediated signals for the conversion of SCLCs into fate-committed SCs, the use of animal cells is clinically unacceptable. To overcome this problem, we previously acquired human induced pluripotent stem cell-derived sensory neurons (hiPSC-dSNs) as surrogates of rat DRG neurons that committed rat bone marrow SCLC to the SC fate.
In this study, we explored whether hiPSC-dSNs could mimic rat DRG neurons effects to obtain fate-committed SCs from hBMSC-derived SCLC.
Methods
hiPSCs were induced into hiPSC-dSNs using a specific chemical small molecules combination. hBMSCs were induced into hBMSC-derived SCLCs in specific culture medium and then co-cultured with hiPSC-dSNs to generate SCs. The identity of hBMSC-derived SCs (hBMSC-dSCs) were examine by immunofluorescence, western bolt, electronic microscopy, and RNA-seq. Immunofluorescence was also used to detect the myelination capacity. Enzyme-Linked Immunosorbant Assay and neurite outgrowth analysis was used to test the neurotrophic factors secretion.
Results
The hBMSC-dSCs exhibited bi-/tri-polar morphology of SCs and maintained the expression of the SC markers S100, p75NTR, p0, GFAP, and Sox10, even after withdrawing the glia-inducing factors or hiPSC-dSNs. Electronic microscopy and RNA-seq analysis provided evidence that hBMSC-dSCs were similar to the original human SCs in terms of their function and a variety of characteristics. Furthermore, these cells formed MBP-positive segments and secreted neurotrophic factors to facilitate the neurite outgrowth of Neuro2A.
Conclusions
These results demonstrated that phenotypically stable and functionally mature hBMSC-dSCs were generated efficiently via the co-culture of hiPSC-dSNs and hBMSC-derived SCLCs. Our findings may provide a promising protocol through which stable and fully developed hBMSC-dSCs can be used for transplantation to regenerate myelin sheath.
Improving 7th grade students’ understanding of how science works
Authors: Reich Norbert , Wang Yuedong 
Published: September 2024

Abstract

We examined the effectiveness of the SciTrek outreach program involving two junior high teachers in the same school. SciTrek has run modules in 2nd -8th grade classrooms since 2010, with each classroom participating in two modules per academic year. For this study, students (206) in eight classrooms took part in one 7th grade module focused on conservation of mass lasting six days during the Fall, and a different module focused on cellular respiration and lasting eight days in the Winter. Students took a pre-assessment prior to the modules to determine their ability to identify a testable question, to plan and design an experimental investigation, to analyze and interpret data with computational thinking. Upon finishing both modules, students took the same assessment. Students improved significantly in all aspects, showing improvements of 10–45%. Students with lower academic performance (College Preparatory, three classrooms) improved more and showed more variability in their improvement than those with higher prior academic performance (Honors). The population included socioeconomically disadvantaged (57%) and Hispanic or Latino (64%) students. We discuss the importance of key features of the approach: the inclusion of four to six trained university volunteers in each classroom to guide small group discussions, and the active engagement of the 7th grade students in developing their own questions, designing their own experiments, data collection, and the defense of their conclusion to their peers.
Unveiling Fine-scale Spatial Structures and Amplifying Gene Expression Signals in Ultra-Large ST slices with HERGAST
Authors: Yu Zhangsheng , Gong Yuqiao , Yuan Xin , Jiao Qiong 
Published: September 2024

Abstract

We propose HERGAST, a system for spatial structure identification and signal amplification in ultra-large-scale and ultra-high-resolution spatial transcriptomics data. To handle ultra-large data, we devise a Divide-Iterate-Conque strategy and construct a heterogeneous graph network to incorporate both local and global spatial relationships. HERGAST's high-precision spatial clustering enabled finding SPP1+ macrophages intermingled in tumors in colorectal cancer, while the enhanced gene expression signal enabled discovering unique spatial expression pattern of key genes in breast cancer.
The impact of environmental regulations on carbon emissions in countries with different levels of emissions
Authors: Borowiec Justyna , Papież Monika , Śmiech Sławomir 
Published: September 2024

Abstract

The study analyses the impact of environmental regulations on carbon emissions in countries with different levels of emissions, utilising two measures of carbon emissions based on: production (PBA) and consumption (CBA) accounting. Environmental regulations are measured by means of three components of the Environmental Policy Stringency (EPS) index: market-based and non-market-based instruments, and technology support. The Moments-Quantile Regression method is employed to assess the effectiveness of these policies across countries with varying levels of emissions—high, medium, and low. The findings indicate that increased stringency in environmental regulations correlates with reduced carbon emissions per capita. Notably, the EPS index has a more significant effect on reducing PBA emissions compared to CBA emissions. A key finding is that the EPS index is more effective in countries with lower pollution per capita (i.e., lower quantiles) than in those with higher pollution per capita. Among the three components, market-based instruments are identified as the most effective in reducing carbon emissions. Additionally, in countries where per capita emissions are relatively low, the combination of market and non-market instruments proves to be the most effective in reducing emissions. In contrast, the highest carbon emitters per capita tend to achieve emissions reductions primarily through technological support.
Small-Scale, Long-Duration, and Biodegradable Zinc-Air Batteries
Authors: Zhang Jingwen , Allen Mark 
Published: September 2024

Abstract

The Internet of Things (IoT) consists of multiple networked nodes, typically comprising transducers and communication capability, that collect and exchange data to achieve a system goal. As IoT node adoption increases, the impact of e-waste on the environment must be considered. Many IoT nodes are therefore incorporating biodegradable MEMS sensors. A recent example is that of precision agricultural systems, in which biodegradable IoT nodes are placed on or below the soil to monitor the plant environment over timescales from weeks to months. Such nodes require energy sources that also biodegrade without harm to the environment. Herein we report Zn-air batteries fabricated from biodegradable materials, and characterize battery performance under sensor-relevant power requirements. The battery comprises a biodegradable Zn anode, a hydrogel electrolyte, and an air cathode (normally consisting of a gas diffusion layer and a catalyst layer). Battery dimensions studied range from 2x2x0.7 cm3 (large cell) to 10x8x5 mm3 (corn cell, approximately the size of a corn kernel). A scalable biowax encapsulation process was developed for battery passivation. A variety of hydrogel compositions and corrosion inhibitors were investigated to extend battery lifetime. Under discharge, large cell peak power densities ranging from 10 to 50 mW/cm2, and lifetimes ranging from 15 days to 340 days, were achieved. Similarly, corn cell peak power densities ranging from 6.5 to 7.5 mW/cm2, and lifetimes ranging from 7 days to 82 days were achieved. Battery operation was measured both in air and soil environments, showing the potential of this approach for environmental IoT applications.
Metformin inhibits melanin synthesis and melanosome transfer through the cAMP pathway
Authors: Liu Xing , Sun Xiaojie , Liu Yunyao , Wang Wenzhu , Yang Hedan , Ge Yiping , Yang Yin , Chen Xu , Lin Tong 
Published: September 2024

Abstract

Several studies have demonstrated the inhibitory effect of metformin on pigmentation. However, the effect of metformin on melanosome transfer remains unknown. The goals of this study were to elucidate the effects of metformin on melanogenesis and melanosome transfer and explore the related mechanisms. We determined that, compared with those in the control zebrafish, the area occupied by pigment granules, melanin content, tyrosinase activity, and the expression levels of melanogenesis genes and melanosome transfer-related genes were reduced in metformin-treated zebrafish. In human primary melanocytes, MNT1 cells/B16F10 cells, metformin also plays a negative role in melanin synthesis regardless of health status and α-MSH-induced pigmentation. Unlike arbutin, metformin inhibited the formation of dendrites and filopodia-like structures and suppressed melanosome transfer. After treatment with metformin, the cAMP content was reduced, the expression of MITF and downstream molecules was downregulated, and the expression of Rho GTPases was changed. Furthermore, metformin partially abrogated the changes in genes regulating melanin synthesis, melanosome transfer and the cytoskeleton induced by a cAMP activator. Our study revealed that metformin can serve as a candidate depigmentation agent.
Evaluating the effectiveness of different media for wildfire information dissemination under multiple scenarios in eight provinces of China
Authors: Duo Meng , Hu Jun , Ni Xiaoyong , Yang Yongsheng , Chen Anying 
Published: September 2024

Abstract

During a wildfire, timely dissemination of disaster information is crucial in reducing the public's exposure to hazards and allowing for early adoption of necessary precautions and safe evacuation. However, ensuring the timely dissemination of information presents a great challenge in the event of a great wildfire. This study aims to assess the effectiveness of several information dissemination channels, including Short Messaging Service (SMS), Television (TV), online social networks, and offline disaster information officers under multiple wildfire scenarios comprehensively, focusing on eight provinces with high wildfire risk in China. By using statistical data, the study dynamically fits the usage of different information media to analyze the information coverage over time under multiple wildfire scenarios, including daytime information release, nighttime information release and signal interruption. The results of the study show that the SMS channel has the fastest dissemination speed and the largest number of recipients, and disaster information officers will play an important role in the case of paralyzed communication facilities. While TV is less effective than online social media in disseminating information, it remains a key channel for some areas. These findings can assist relevant authorities to choose the appropriate information dissemination channels under different scenarios to ensure that pre-warning information can be delivered to the public in a timely and efficient manner, thus reducing the losses and risks associated with wildfires.
Tetrahedral versus Octahedral Interstitials Sites for Oxygen Solutes in NbTiZr Medium-Entropy Alloy
Authors: Ding Jun , Zhang Bozhao , An Yaqiong , Liu Chang , Ma En 
Published: September 2024

Abstract

Oxygen interstitial solutes have traditionally been thought to occupy only octahedral interstices in body-centered cubic (bcc) metals. However, there is ongoing debate about the competition between tetrahedral and octahedral interstitial sites for oxygen solutes in multi-principal element alloys, especially following recent experimental evidence obtained using deep-sub-angstrom-resolution electron ptychography. The driving force and atomistic mechanism behind the observed preference switch remain unclear. In this study, we systematically investigate the competition between tetrahedral and octahedral sites for oxygen, nitrogen, and carbon solute atoms in bcc NbTiZr alloys using density functional theory calculations. At dilute concentrations, these small interstitial solutes are observed to preferentially reside in octahedral interstices. Notably, we demonstrate that solutes can switch from octahedral to tetrahedral sites with increasing lattice expansion, interstitial solute concentration, and spatial heterogeneity. This transition is explained by a crossover in elastic strain energy associated with solutes in the two competing interstices. Our findings provide a deeper understanding of the behavior of small interstitial solutes and their solid solution strengthening effects in bcc multi-principal element alloys.
Prophylactic efficacy and safety evaluation of locally isolated strain Levilactobacillus brevis (MF179529), commercial probiotics and yeast: A comparison
Authors: Riaz Ayesha , Abbas Safeer , Arshad Muhammad , Arshad Najma , Shah Anis Ali , Iftikhar Muhammad , Shaffique Shifa , Gatasheh Mansour K. 
Published: September 2024

Abstract

Aims:To anticipate the ban on antibiotic growth promoters in poultry researchers are trying to find safe alternatives from natural resources. The probiotics of Lactobacillus genus are among the promising candidates. The efficacy of probiotics is considered species, strain and source specific. In this study Levilactobacillus brevis, MF179529 comparison was performed with commercial probiotic and yeast.
Methods and results: This study provides a comparison of safety and prophylactic efficiency of (i) locally isolated potential probiotic strain, L. brevis, MF179529, (ii) commercial probiotics, Floramix plus , (iii) yeast, Saccharomyces cerevisiae and (iv) their two combinations on limiting avian pathogenic E. coli (APEC) induced colibacillosis in chicken. All probiotics inhibited infection induced anemia but results were more pronounced in groups I. Birds of group I displayed significantly (p < 0.05) higher general health scores, lower mortality and tissue bacterial load. APEC infection leads to reduction in relative weight of spleen. However, all probiotic treated groups displayed relatively normal spleen weight.
Conclusion:Animals receiving L. brevis MF179529 displayed lower blood cholesterol (p < 0.05), which might be considered a favorable characteristic of meat quality. No adverse effects were observed in other hematological and serological parameters.
Significance of study: L. brevis MF179529 and its combination with commercial probiotics is a better and safe alternative of antibiotic growth promoters in poultry.
Long Short-Term Memory based fault tolerance control: an intelligent approach to control a system efficiently exposed to faults.
Authors: El-Mahdy Mostafa H. , Ali Abdelrahman O. , Hassan O. H. , El_Gendy Eman M. , Saafan Mahmoud M 
Published: September 2024

Abstract

Fault-Tolerant Control (FTC) is a crucial field within control systems engineering that focuses on designing systems capable of maintaining desired performance and stability even in the presence of faults. This study introduces a data-driven fault-tolerant control system that enhances the operation of control systems in the presence of faults. The system is designed on a single Long Short-Term Memory (LSTM), which replaces the units responsible for diagnosis and control reconfiguration. The LSTM-FTC system does not require diagnostic and process models, which is a significant advantage over traditional model-based methods. The factory I/O is interfaced with MATLAB through the implementation of the digital twin idea, which allows for the simulation and validation of the suggested approaches. These approaches are then applied to an assembler case study that included both faultless and multiple faulty sensors. The training process reaches 6553 iterations with Root Mean Square Error (RMSE) equal to \(\:5\times\:{10}^{-3}\) at six minutes and 17 seconds. The results of the simulation demonstrate the effectiveness of the proposed approaches. The accuracy of the system outputs in the faultless and worst-case scenarios are 92.81% and 67.16% respectively.