bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying methods to reduce emission intensity of centralised Photovoltaic deployment for net zero by 2050: Life cycle assessment case study of a 30 MW PV plant
Authors: Kim Moonyong , Drury Storm , Altermatt Pietro , Wang Li , Zhang Yuchao , Chan Catherine , Dias Pablo , Hallam Brett 
Published: October 2023

AbstractPhotovoltaics (PV) is one of the most effective and necessary energy sources to mitigate climate change. The broad electrification scenario projects the PV market to grow from 1 TW in 2022 to over 63 TW in 2050. While increasing PV production will significantly reduce the emission intensity of electricity generation, it is still important to minimise the overall environmental impact of such a large industry. In this study, we investigated the intensity of greenhouse gas (GHG) emissions of a 30 MW PV plant using a life cycle assessment (LCA). Based on the LCA, we propose a roadmap to reduce emissions from PV manufacturing and deployment. Decarbonising significant factors like aluminium and concrete production or the electricity demand to produce PV modules can greatly reduce the carbon budget related to PV production. Our study shows that the global warming potential (GWP) per kWh can be reduced from 11.2 to 1.7 g CO2‐eq/kWh over the lifetime of the PV system (85% reduction). Using the aspects to decarbonise PV production, the roadmap is demonstrated. The cumulative GWP to reach 63 TW is initially estimated to be 44 Gt CO2‐eq. Our decarbonising roadmap demonstrated that such significance can be reduced by over 37 Gt CO2‐eq, equivalent to a whole year emission in year 2022.
Assembled polyphenol‐based systems as advanced therapeutics
Authors: Liu Tao , Pan Pei , Shi Hui , Feng Jun , Zhang Xian‐Zheng 
Published: October 2023

AbstractPolymeric assemblies have emerged as a kind of promising platform in biomedical fields. The strong potency of polyphenols to form versatile interactions with other small or polymeric molecules via covalent and noncovalent linkages enables polyphenols to serve as molecular glues, offering a magic driving force to assemble multiple functional molecules into a diversity of polyphenol‐based systems, such as nanoparticles and hydrogels. Due to the unique merits of anti‐tumor, anti‐bacterial, antioxidant, anti‐inflammatory, and cardioprotective properties of polyphenols, polyphenol‐based systems hold great promise to deal with a wide spectrum of diseases. This review comprehensively overviews the components, intermolecular interactions, and preparation methods implicated in the assembly of polyphenol‐based systems. In addition, their medical applications are introduced, particularly the treatments of various diseases, such as tumors, bacterial infections, inflammatory bowel disease (IBD), cardiovascular diseases (CVDs), chronic periodontitis, acute lung injury, osteoarthritis, and renal fibrosis.
A city of two tales: Educational gradients of discrimination experiences among internal migrants in Beijing, China
Authors: Mu Zheng , Lee Nicol Si Jie 
Published: October 2023

AbstractDrawing on 127 qualitative in‐depth interviews in Beijing, China in 2015, we examine the similarities and differences in discrimination experiences among internal migrants across educational backgrounds. While institutional discrimination remains a significant barrier for both university‐educated and lower‐educated migrants, findings reveal a salient educational differential in the experiences of social discrimination. The reduction in social discrimination enjoyed by university‐educated migrants arises from a shared class identity between them and the locals due to similar cultural and socioeconomic backgrounds. Moreover, results show a divide among migrants across education and socioeconomic status. In an attempt to distance themselves from their fellows of lower socioeconomic status, university‐educated migrants and migrants of higher socioeconomic status turn towards in‐group discrimination, based on perceived differentials in skills and entitlements to Beijing's resources. This study highlights the importance of unpacking the nuanced patterns and pathways across educational and socioeconomic heterogeneities in examining migrants' discrimination experiences.
Atractylenolide I improves behaviors in mice with depression‐like phenotype by modulating neurotransmitter balance via 5‐HT2A
Authors: Pei Hongyan , Du Rui , He Zhongmei , Bi Jinhao , Zhai Liping , Shen Heping 
Published: October 2023

AbstractTo explore the antidepressant effects and targets of atractylenolide I (ATR) through a network pharmacological approach. Relevant targets of ATR and depression analyzed by network pharmacology were scored (identifying 5‐HT2A targets). Through elevated plus maze, open field, tail suspension, and forced swimming tests, the behavioral changes of mice with depression (chronic unpredictable mild stress [CUMS]) were examined, and the levels of neurotransmitters including serotonin, dopamine, and norepinephrine (5‐HT, DA, and NE) were determined. The binding of ATR to 5‐HT2A was verified by small molecular‐protein docking. ATR improved the behaviors of CUMS mice, elevated their levels of neurotransmitters 5‐HT, DA, and NE, and exerted a protective effect on their nerve cell injury. After 5‐HT2A knockout, ATR failed to further improve the CUMS behaviors. According to the results of small molecular‐protein docking and network pharmacological analysis, ATR acted as an inhibitor by binding to 5‐HT2A. ATR can improve the behaviors and modulate the neurotransmitters of CUMS mice by targeting 5‐HT2A.
Stimuli‐responsive active materials for dynamic control of light field
Authors: Zheng Ren , Wei Yang , Zhang Zi‐Chen , Wang Ze‐Yu , Ma Ling‐Ling , Wang Yu , Huang Ling , Lu Yan‐Qing 
Published: October 2023

AbstractThe increasing demand for the multidimensional and dynamic control of light has spurred the development of stimuli‐responsive, reconfigurable, and programmable optical systems. Liquid crystals (LCs), which combine liquid‐like stimuli‐responsiveness and crystal‐like orientational ordering, have emerged as highly appealing soft materials. Owing to their exceptional optical performance and programmable functionalities, they are becoming incredibly important materials in active planar optics and photonics. Additionally, silk proteins, luminescent materials, and metasurfaces exhibit dynamic optical properties, enabling remarkable multifunctional applications. This review focuses on the advancements in stimuli‐responsive materials, including LCs, silk proteins, luminescent materials, and active metasurfaces as well as some of these materials paired with LCs. Their attractive tunable applications in optics and photonics, along with the great potential for the future development of active optical systems, are also emphasized.
Plant species and soil depth differentially affect microbial diversity and function in grasslands
Authors: Ryan Kerry B. , De Menezes Alexandre , Finn John A. , Brennan Fiona P. 
Published: October 2023

AbstractIntroductionGrassland ecosystems are a major store of terrestrial carbon (C), yet little is known about their capacity to cycle and store C in deeper soil horizons. Further, it is unclear how plant community composition within agricultural grasslands mediates this capacity and influences microbial community composition. We investigated whether the aboveground community composition in intensively managed agricultural grasslands influenced belowground microbial community composition, abundance, respiration and enzyme activities with depth.Materials and MethodsSoil was sampled in four soil layers: A (0–15 cm), B (15–30 cm), C (30–60 cm) and D (60–90 cm) in monocultures of six grassland species and a mixture of all six. Functional capacity was measured through enzymatic and substrate‐induced respiration assays, and microbial abundance and diversity were assessed via quantitative polymerase chain reaction and sequencing (16S, Internal transcribed spacer), respectively.ResultsMicrobial abundance and C cycling enzyme activity decreased and community composition changed, along the soil depth gradient, regardless of the plant community. Microbial abundance was not significantly influenced by plant community type across the entire soil depth profile. However, prokaryotic community composition was significantly influenced by plant community in the top 15 cm of soil, and fungal community composition was significantly influenced between 15 and 30 cm in depth. Plant community types mediated the rate at which C cycling enzyme activity decreased along the soil depth gradient, and selected C cycling enzymes were significantly more active at 15–60 cm depth when Cichorium intybus (a deep rooting species) was present.ConclusionThis study provides an improved understanding of how agricultural grassland communities affect the soil microbiome with depth; this has potential implications for the management of these systems for enhanced soil health. Our work indicates the potential for multispecies mixtures with deep rooting species to be a practical strategy to increase C cycling capacity in deeper soil layers within grasslands, which may have implications for policy goals related to C storage.
Visible Light Responsive Soft Actuator Based on PVA‐DR1
Authors: Saifi Anas , Negi Charu , Singh Atul Pratap , Kumar Kamlesh 
Published: October 2023

AbstractThere is a growing interest in creating biomimetic actuators that can perform human‐like actions in response to external stimuli. Despite the significant advancements in soft actuators, using high‐energy UV light in photoresponsive actuators remains a great challenge. Herein, we develop a film composed of polyvinyl alcohol and photo responsive Disperse Red 1 (PVA/DR1) that actuate in response to visible light. The photoresponsive film starts to actuate in the presence of green light due to trans→cis isomerization of photoresponsive dye. The actuation response of the films was investigated by varying concentrations of DR1 dye and the intensity of green light. Based on these features, we demonstrated a four‐arm soft‐gripper that can mimic human‐hand‐like motions in response to green light. This kind of actuator may find potential applications in soft robotics and biomimetic microgrippers.
Tuning Main Group Element‐based Metal–Organic Framework to Boost Electrocatalytic Nitrogen Reduction Under Ambient Conditions
Authors: Han Bo , Zhong Lixiang , Chen Cailing , Ding Jie , Lee Carmen , Liu Jiawei , Chen Mengxin , Tso Shuen , Hu Yue , Lv Chade , Han Yu , Liu Bin , Yan Qingyu 
Published: October 2023

AbstractMain group element‐based materials are emerging catalysts for ammonia (NH3) production via a sustainable electrochemical nitrogen reduction reaction (N2RR) pathway under ambient conditions. However, their N2RR performances are less explored due to the limited active behavior and unclear mechanism. Here, an aluminum‐based defective metal–organic framework (MOF), aluminum‐fumarate (Al‐Fum), is investigated. As a proof of concept, the pristine Al‐Fum MOF is synthesized by the solvothermal reaction process, and the defect engineering method namely solvent‐assisted linker exchange, is applied to create the defective Al sites. The defective Al sites play an important role in ensuring the N2RR activity for defective Al‐Fum. It is found that only the defective Al‐Fum enables stable and effective electrochemical N2RR, in terms of the highest production rate of 53.9 µg(NH3) h−1mgcat−1 (in 0.4 m K2SO4) and the Faradaic efficiency of 73.8% (in 0.1 m K2SO4) at −0.15 V vs reversible hydrogen electrode) under ambient conditions. Density functional theory calculations confirm that the N2 activation can be achieved on the defective Al sites. Such sites also allow the subsequent protonation process via the alternating associative mechanism. This defect characteristic gives the main group Al‐based MOFs the ability to serve as promising electrocatalysts for N2RR and other attractive applications.
Verification and validation of software process simulation models: A systematic mapping study
Authors: Li Yue , Zhang He , Liu Bohan , Dong Liming , Gong Haojie , Rong Guoping 
Published: October 2023

AbstractSoftware process simulation models (SPSMs) that are based on descriptive process models offer the executability that can demonstrate dynamic changes of software processes over time. Verification and validation (V&V) is critical in SPSMs for guaranteeing the quality and reliability of models. V&V of dynamic software process models is more complex and challenging than for static software process models. This work systematically summarizes and maps V&V studies in SPSM to provide guidelines for future research and practice. Specifically, this study aims at identifying the focus of research on V&V, the methods used for V&V, and how to implement V&V of SPSMs in software engineering research. We conducted a systematic mapping study on studies of SPSMs that report on their V&V activities. Under the guidance of a V&V meta‐model for SPSMs, we study four research questions about V&V process. We identified 107 primary studies from a pool of 313 papers on SPSMs until 2021. There are two main results of our study. The first one presents the relationship between quality aspects of SPSMs and the V&V methods to assure them. The second result reveals the relationships among the modeling process, three modeling steps, five quality aspects, and 10 V&V methods. Generally, researchers do not pay sufficient attention to V&V, as 65.8% ( ) failed to mention or elaborate on their V&V process. We systematically summarize and map the state‐of‐the‐art V&V research in software process modeling field to support modelers' practice and improve their V&V process.
Code smells in pull requests: An exploratory study
Authors: Azeem Muhammad Ilyas , Shafiq Saad , Mashkoor Atif , Egyed Alexander 
Published: October 2023

AbstractThe quality of a pull request is the primary factor integrators consider for its acceptance or rejection. Code smells indicate sub‐optimal design or implementation choices in the source code that often lead to a fault‐prone outcome, threatening the quality of pull requests. This study explores code smells in 21k pull requests from 25 popular Java projects. We find that both accepted (37%) and rejected (44%) pull requests have code smells, affected mainly by god classes and long methods. Besides, we observe that smelly pull requests are more complex and challenging to understand as they have significantly large sizes, long latency times, more discussion and review comments, and are submitted by contributors with less experience. Our results show that features used in previous studies for pull request acceptance prediction could be potentially employed to predict smell in incoming pull requests. We propose a dynamic approach to predict the presence of such code smells in the newly added pull requests. We evaluate our approach on a dataset of 25 Java projects extracted from GitHub. We further conduct a benchmark study to compare the performance of eight machine learning classifiers. Results of the benchmark study show that XGBoost is the best‐performing classifier for smell prediction.
Professionalization in student affairs and services across the globe
Authors: Perozzi Brett , Shea Robert 
Published: October 2023

AbstractThis article explores the concept of Student Affairs and Services (SAS) as a global profession, how it is positioned and positions itself in the context of what it means to be a profession and reflects on the ways in which SAS has and can professionalize. The literature related to professionalization is presented along with a discussion of the outcomes of the review, which provides direction for SAS as a global profession.
Detection of synthetic lipid‐lowering adulterants in herbal products using high‐performance thin‐layer chromatography
Authors: Joshi Hardi , Bahliwala Payal , Vadalia Jigna , Vegad Udaykumar 
Published: October 2023

AbstractAdulterating herbal medicine with undeclared synthetic drugs is a worldwide problem that seriously threatens human health. To detect such illicit and not labeled synthetic hypolipidemic substances in herbal medicines, an analytical method to simultaneously identify and quantify atorvastatin (ATV) calcium, simvastatin (SIM), gemfibrozil (GEM), fenofibrate (FEN) belonging to two different classes of drugs (statins and fibrates) was developed based on high‐performance thin‐layer chromatography. The method consisted of Silica Gel G60 F254 precoated aluminum plate as stationary phase and toluene: ethyl acetate: formic acid (7:3:0.3, v/v/v) as optimized mobile phase. The densitometric evaluation wavelength was optimized at 254 nm. The Rf values of ATV, SIM, GEM, and FEN were 0.157, 0.268, 0.691, and 0.852, respectively. The linearity range is between 100–1500 ng/band for ATV and FEN and 200–3000 ng/band for SIM and GEM, respectively. The accuracy was found to be in the range of 97%–105%. The relative standard deviation of precision and robustness was found to be < 5%. However, the five screened market samples did not show the presence of adulteration of the above drugs. This method for the simultaneous determination of four drugs may be successfully employed to screen synthetic hypolipidemics as adulterants in herbal products and dietary supplements.
Effect and molecular mechanism of Sulforaphane alleviates brain damage caused by acute carbon monoxide poisoning:Network pharmacology analysis, molecular docking, and experimental evidence
Authors: Yue Ao‐Chun , Zhou Xu‐Dong , Song Hui‐Ping , Liu Xu‐Han , Bi Ming‐Jun , Han Wei , Li Qin 
Published: October 2023

AbstractSulforaphane (SFN) has attracted much attention due to its ability on antioxidant, anti‐inflammatory, and anti‐apoptotic properties, while its functional targets and underlying mechanism of action on brain injury caused by acute carbon monoxide poisoning (ACOP) have not been fully elucidated. Herein, we used a systematic network pharmacology approach to explore the mechanism of SFN in the treatment of brain damage after ACOP. In this study, the results of network pharmacology demonstrated that there were a total of 81 effective target genes of SFN and 36 drug–disease targets, which were strongly in connection with autophagy–animal signaling pathway, drug metabolism, and transcription disorders in cancer. Upon the further biological function and KEGG signaling pathway enrichment analysis, a large number of them were involved in neuronal death, reactive oxygen metabolic processes and immune functions. Moreover, based on the results of bioinformatics prediction associated with multiple potential targets and pathways, the AMP‐activated protein kinase (AMPK) signaling pathway was selected to elucidate the molecular mechanism of SFN in the treatment of brain injury caused by ACOP. The following molecular docking analysis also confirmed that SFN can bind to AMPKα well through chemical bonds. In addition, an animal model of ACOP was established by exposure to carbon monoxide in a hyperbaric oxygen chamber to verify the predicted results of network pharmacology. We found that the mitochondrial ultrastructure of neurons in rats with ACOP was seriously damaged, and apoptotic cells increased significantly. The histopathological changes were obviously alleviated, apoptosis of cortical neurons was inhibited, and the number of Nissl bodies was increased in the SFN group as compared with the ACOP group (p < .05). Besides, the administration of SFN could increase the expressions of phosphorylated P‐AMPK and MFN2 proteins and decrease the levels of DRP1, Caspase3, and Casapase9 proteins in the brain tissue of ACOP rats. These findings suggest that network pharmacology is a useful tool for traditional Chinese medicine (TCM) research, SFN can effectively inhibit apoptosis, protect cortical neurons from the toxicity of carbon monoxide through activating the AMPK pathway and may become a potential therapeutic strategy for brain injury after ACOP.
A novel collaborative control algorithm for maximum power point tracking of wind energy hydraulic conversion system
Authors: Chen Lijuan , Li Jingbin , Zhang Lin , Gao Wei , Ai Chao , Ding Beichen 
Published: October 2023

AbstractWind has been admitted as one of the most promising renewable energy resources in multinational regionalization policies. However, the energy conversion and utilization are challenging due to the technique reliability and cost issues. Hydraulic wind turbine (HWT) may solve the above problems. HWT is taken as a research object, and the maximum power point tracking (MPPT) control strategy is proposed collaborating with active disturbance rejection control (ADRC) and linear quadratic regulator (LQR) control methods, to solve multiplicative nonlinearity problems in the plant models and the influence of external disturbance on control performance in the MPPT control process. A nonlinear simulation model is built to explain the main findings from the experiments and obtain a better understanding of the effect of time‐varying system parameters and random fluctuation in wind speed. The collaborative control algorithm is experimentally verified on a 24‐kW HWT semi‐physical test platform that results in a promising energy conversion rate, plus the hydraulic parameters can satisfy the demand, accordingly. Ultimately, the potential challenges of implementing this technique in a smart wind energy conversion system are discussed to give a further design guidance, either theoretically or practically.
Magnetic field and dissipation effects on mixed convection viscous fluid flow by a channel in the presence of porous medium and heat generation/absorption phenomenon
Authors: Xin Xiao , Masthanaiah Y. , Rushikesava A. , Tarakaramu Nainaru , Abdullaev Sherzod , Khan M. Ijaz , Bouazzi Imen Rashid 
Published: October 2023

AbstractIn this study, we investigate the phenomenon of mixed convection in viscous fluid flow by a vertical channel, considering the presence of magneto‐hydro‐dynamics and porosity. Mixed convection occurs when both buoyancy forces and external forces, such as pumps or fans, influence the flow behavior. Understanding and accurately predicting mixed convection is crucial for optimizing heat exchanger design and performance. To model the temperature equation, we utilize the concept of the first law of thermodynamics. Additionally, we incorporate effects such as Joule heating, heat generation, and radiative heat flux in the energy equation modeling. The resulting physical liquid equations are solved using the shooting technique with the RKF (Runge–Kutta–Fehlberg) scheme. We present graphical representations of the flow variables, discussing their behavior in detail. The introduction provides an overview of the paper's roadmap, while the conclusion highlights the main and significant results obtained from our study. We found that, the temperature is more when liquid motion in between channel for large numerical values of thermal radiation parameter and Reynolds number.