bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of sodium hydroxide, sodium dodecyl benzenesulfonate, and resin on the interfacial tension of asphaltenic synthetic oil extracted from acidic crude oil under low salinity condition
Authors: Abbood Nabeel K. , Dahham Nawfal Adnan , Dezfouli Mohammad Assarehzadegan , Hosseini Seyednooroldin 
Published: July 2023

AbstractDuring the past years, the usage of new oil recovery methods known as enhanced oil recovery methods is increasing because of energy consumption rate enhancement and reservoir pressure depletion. Unfortunately, since most of the investigations were focused on crude oil, it is hard to find a generalized pattern of interfacial tension (IFT) and wettability change for different crude oils because of its complicated composition. So, it is necessary to examine the effect of specific fractions of crude oil especially resin and asphaltene fractions on the IFT and wettability alteration using systematic investigations. Although a limited number of investigations examined the interactions between these specific fractions and salts, there are no systematic reports respecting the possible interactions between asphaltene and resin fractions in the presence of alkaline and surfactant. So, in the first stage, the impact of dissolving asphaltene (0–9 wt%) in the toluene was investigated on the IFT reduction which revealed a decrease in IFT value from 34.8 to 23.3 mN/m as the asphaltene concentration was increased. Further experiments showed that the presence of MgCl2 and NaCl with a maximum concentration of 5000 ppm led to a reduction in IFT to a minimum value of 18.3 and 17.3 mN/m for NaCl and MgCl2, respectively, which means the higher impact of MgCl2 on the IFT reduction. After that, the selected optimum concentrations of MgCl2 and NaCl (5000 ppm) were used in the rest of the experiments in which the effect of resin fraction and other chemicals including sodium dodecyl benzenesulfonate (SDBS) and NaOH concentrations was examined on the IFT reduction and rock wettability. According to the obtained results, it was possible to reach the minimum IFT value of 0.08 mN/m, which is several orders lower than the original IFT value of the binary system without the chemicals using the optimum chemical formulation obtained by mixing proper concentrations of SDBS, NaOH, MgCl2, and NaCl. Moreover, the obtained optimum formulations were used through core flooding experiments which revealed the possibility of increasing the oil recovery to a maximum value of 10.1% based on the original oil in place.
Towards a Pragmatic and Pluralist Framework for Energy Justice
Authors: Laes Erik , Bombaerts Gunter , Spahn Andreas 
Published: July 2023

AbstractThe three-tenet model, which focuses on ‘distributional justice’, ‘procedural justice’, and ‘justice as recognition’, has emerged as the most influential framework in the field of energy justice. Based on critical reviews of the three-tenet model, we identify three challenges that the model currently still faces: (i) a normative challenge on the grounding of the three-tenet model in philosophical theories; (ii) an ‘elite’ challenge on the justification of the use of power in energy-related decision; and (iii) a practical challenge on the application of the three tenets in situations of conflicting justice demands. In this article, we provide the basic contours of a three-step pluralist and pragmatic dialogue model for questions of energy justice that addresses the three challenges, based on the ‘commonwealth model’ of Luc Boltanski and Laurent Thévenot. The model proposes to create moral legitimacy in the face of plural demands for energy justice by engaging actors in an inclusive dialogue based on an explicit recognition of Boltanski and Thévenot’s commonwealth model. We thereby make three contributions to the existing literature on energy justice. First, the commonwealth model’s rootedness in normative political theory provides a stronger philosophical underpinning than was available up till now in the literature (challenge 1). Second, it allows one to go beyond the (almost exclusive) focus on injustices perpetrated on disempowered or marginalised groups, to include questions on the justified exercise of power (challenge 2). Third, the commonwealth model shows us practical ways out of situations where conflicting demands for justice are being made (challenge 3).
Targeted CRISPR activation and knockout screenings identify novel doxorubicin transporters
Authors: Li Yufeng , Tan Minkang , Sun Shengnan , Stea Elena , Pang Baoxu 
Published: July 2023

Abstract
Purpose
Tissue-specific drug uptake has not been well studied, compared to the deeper understanding of drug resistance mediated by the cellular efflux system such as MDR1 proteins. It has been suggested that many drugs need active or defined transporters to pass the cell membrane. In contrast to efflux components induced after anti-cancer drugs reach the intracellular compartment, drug importers are required for initial drug responses. Furthermore, tissue-specific uptake of anti-cancer drugs may directly impact the side effects of many drugs when they accumulate in healthy tissues. Therefore, linking anti-cancer drugs to their respective drug import transporters would directly help to predict drug responses, whilst minimizing side effects.

Methods
To identify drug transporters of the commonly used anti-cancer drug doxorubicin, we performed focused CRISPR activation and knockout genetic screens targeting all potential membrane-associated transporters and proteins. We monitored the direct uptake of doxorubicin by fluorescence-activated cell sorting (FACS) as the screening readout for identifying transporters/proteins directly involved in doxorubicin uptake.

Results
Integrating the data from these comprehensive CRISPR screenings, we confirmed previously indicated doxorubicin exporters such as ABCB1 and ABCG2 genes, and identified novel doxorubicin importer gene SLC2A3 (GLUT3). Upregulation of SLC2A3 led to higher doxorubicin uptake and better cell killing, indicating SLC2A3 could be a new marker to predict doxorubicin drug response and minimize side effects for the personalized application of this conventional chemotherapeutic drug.

Conclusions
Our study provides a comprehensive way for identifying drug transporters, as exemplified by the commonly used anti-cancer drug doxorubicin. The newly identified importers may have direct clinical implications for the personalized application of doxorubicin in treating distinct tumors. Our results also highlight the necessity of combining both CRISPR knockout and CRISPR activation genetic screens to identify drug transporters.
Clinico-pathological and gene features of 15 nemaline myopathy patients from a single Chinese neuromuscular center
Authors: Haidong Lv , Yin Liu , Ping Chen , Xianzhao Zheng , Qi Qian , Xiaoli Ma , Zheng Lv , Wenhao Cui , Yaguang Zhou , Qianqian Qu 
Published: July 2023

Abstract
Background
Nemaline myopathy, the most common of the congenital myopathies, is caused by various genetic mutations. In this study, we attempted to investigate the clinical features, muscle pathology and genetic features of 15 patients with nemaline myopathy.

Results
Among the 15 patients, there were 9 (60.00%) males and 6 (40.00%) females, and 9 (60.00%) of them came from three families respectively. The age of seeing a doctor ranged from 9 to 52 years old, the age of onset was from 5 to 23 years old, and the duration of disease ranged from 3 to 35 years. Ten out of the 15 patients had high arched palate and elongated face. Only one patient had mild respiratory muscle involvement and none had dysphagia. Muscle biopsies were performed in 9 out of the 15 patients. Pathologically, muscle fibers of different sizes, atrophic muscle fibers and compensatory hypertrophic fibers could be found, and occasionally degenerated and necrotic muscle fibers were observed. Different degrees of nemaline bodies aggregation could be seen in all 9 patients. The distribution of type I and type II muscle fibers were significantly abnormal in patients with nemaline myopathy caused by NEB gene, however, it was basically normal in patients with nemaline myopathy caused by TPM3 gene and ACTA1 gene. Electron microscopic analysis of 6 patients showed that nemaline bodies aggregated between myofibrils were found in 5(83.33%) cases, and most of them were located near the Z band, but no intranuclear rods were found. The gene analysis of 15 NM patients showed that three NM-related genes were harbored, including 11 (73.33%) patients with NEB, 3 (20.00%) patients with TPM3, and 1 (6.67%) patient with ACTA1, respectively. A total of 12 mutation sites were identified and included 10 (83.33%) mutations in exon and 2(16.67%) mutations in intron.

Conclusions
The clinical phenotype of nemaline myopathy is highly heterogeneous. Muscle pathology shows that nemaline bodies aggregation is an important feature for the diagnosis of NM. NEB is the most frequent causative gene in this cohort. The splicing mutation, c.21522 + 3A > G may be the hotspot mutation of the NEB gene in Chinese NM patients.
MT$$^2$$AD: multi-layer temporal transaction anomaly detection in ethereum networks with GNN
Authors: Han Beibei , Wei Yingmei , Wang Qingyong , Collibus Francesco Maria De , Tessone Claudio J. 
Published: July 2023

AbstractIn recent years, a surge of criminal activities with cross-cryptocurrency trades have emerged in Ethereum, the second-largest public blockchain platform. Most of the existing anomaly detection methods utilize the traditional machine learning with feature engineering or graph representation learning technique to capture the information in transaction network. However, these methods either ignore the timestamp information and the transaction flow direction information in transaction network or only consider single transaction network, the cross-cryptocurrency trading patterns in Ethereum are usually ignored. In this paper, we introduce a Multi-layer Temporal Transaction Anomaly Detection (MT$$^2$$

2

AD) model in Ethereum network with graph neural network. Specifically, for a given Ethereum token transaction network, we first extract its initial features including the structure subgraph and edge’s feature. Then, we model the temporal information in subgraph as a series of network snapshots according to the timestamp on each edge and time window. To capture the cross-cryptocurrency trading patterns, we combine the snapshots from multiple token transactions at a given timestamp, and we consider it as a new combined graph. We further use the graph convolution encoder with attention mechanism and pooling operation on this new graph to obtain the graph-level embedding, and we transform the anomaly detection on dynamic multi-layer Ethereum transaction networks as a graph classification task with these graph-level embeddings. MT$$^2$$

2

AD can integrate the transaction structure feature, edge’s feature and cross-cryptocurrency trading patterns into a framework to perform the anomaly detection with graph neural networks. Experiments on three real-world multi-layer transaction networks show that the proposed MT$$^2$$

2

AD (0.8789 Precision, 0.9375 Recall, 0.4987 FbMacro and 0.9351 FbWeighted) can achieve the best performance on most evaluation metrics in comparison with some competing approaches, and the effectiveness in consideration of multiple tokens is also demonstrated.
Evaluating the authenticity of ChatGPT responses: a study on text-matching capabilities
Authors: Elkhatat Ahmed M. 
Published: July 2023

AbstractAcademic plagiarism is a pressing concern in educational institutions. With the emergence of artificial intelligence (AI) chatbots, like ChatGPT, potential risks related to cheating and plagiarism have increased. This study aims to investigate the authenticity capabilities of ChatGPT models 3.5 and 4 in generating novel, coherent, and accurate responses that evade detection by text-matching software. The repeatability and reproducibility of both models were analyzed, showing that the generation of responses remains consistent. However, a two-sample t-test revealed insufficient evidence to support a statistically significant difference between the text-matching percentages of both models. Several strategies are proposed to address the challenges posed by AI integration in academic contexts; one probable solution is to promote self-transcendent ideals by implementing honor codes. It is also necessary to consider the restricted knowledge base of AI language models like GPT and address any inaccuracies in generated references. Additionally, designing assignments that extract data from imaged sources and integrating oral discussions into the evaluation process can mitigate the challenges posed by AI integration. However, educators should carefully consider the practical constraints and explore alternative assessment methods to prevent academic misconduct while reaping the benefits of these strategies.
›Sprechende‹ Tiere im Zoo: Animation, Empathie und Fiktion in Zoo-Doku-Soaps
Authors: Steen Pamela 
Published: July 2023

ZusammenfassungDer Beitrag beschäftigt sich aus einer tierlinguistischen Perspektive mit ›sprechenden‹ Tieren als kulturellem Phänomen, mit einem Fokus auf Zookommunikation bzw. ›Zootieren‹. Anhand exemplarischer gesprächslinguistischer Analysen wird gezeigt, wie ›Zootiere‹ in einer Zoo-Doku-Soap zum Sprechen gebracht werden, d. h. mit welchen sprachlichen Mitteln der Off-Kommentar die Rede der ›Zootiere‹ animiert. Die tierliche Rede kann (trotz des inhärenten Anthropomorphisierens) authentisch, plausibel oder aber unglaubwürdig erscheinen. Im Zuge der Animation werden tierliche Displays und potenzielle Gedanken und Emotionen oftmals vereindeutigt bzw. einer unkontrollierten Mehrdeutigkeit zum Zwecke einer unterhaltenden Projektion preisgegeben.
Pyglotaran: a lego-like Python framework for global and target analysis of time-resolved spectra
Authors: van Stokkum Ivo H. M. , Weißenborn Jörn , Weigand Sebastian , Snellenburg Joris J. 
Published: July 2023

Abstract
The dynamics of molecular systems can be studied with time-resolved spectroscopy combined with model-based analysis. A Python framework for global and target analysis of time-resolved spectra is introduced with the help of three case studies. The first study, concerning broadband absorption of intersystem crossing in 4-thiothymidine, demonstrates the framework's ability to resolve vibrational wavepackets with a time resolution of ≈10 fs using damped oscillations and their associated spectra and phases. Thereby, a parametric description of the “coherent artifact” is crucial. The second study addresses multichromophoric systems composed of two perylene bisimide chromophores. Here, pyglotaran's guidance spectra and lego-like model composition enable the integration of spectral and kinetic properties of the parent chromophores, revealing a loss process, the undesired production of a radical pair, that reduces the light harvesting efficiency. In the third, time-resolved emission case study of whole photosynthetic cells, a megacomplex containing ≈500 chromophores of five different types is described by a combination of the kinetic models for its elements. As direct fitting of the data by theoretical simulation is unfeasible, our global and target analysis methodology provides a useful ‘middle ground’ where the theoretical description and the fit of the experimental data can meet. The pyglotaran framework enables the lego-like creation of kinetic models through its modular design and seamless integration with the rich Python ecosystem, particularly Jupyter notebooks. With extensive documentation and a robust validation framework, pyglotaran ensures accessibility and reliability for researchers, serving as an invaluable tool for understanding complex molecular systems.

Graphical abstract
Electrical investigation and enhancement of optical, structural, and dielectric properties of flexible PVDF/LiZnVO4 nanocomposites
Authors: Elashmawi I. S. , Ismail A. M. , Abdelghany A. M. , Hegazi M. M. , Yassin A. Y. 
Published: July 2023

AbstractThin polymeric films of poly(vinylidene fluoride) (PVDF) containing variable mass fractions of nanoparticles (LiZnVO4) were successfully synthesized via the ordinary solution casting method. X-ray diffraction (XRD), Fourier transform infrared (FT-IR), and ultraviolet–visible spectroscopy were used to explore the role of LiZnVO4 on the structural and optical characteristics of synthesized nanocomposites. In addition, dielectric permittivity (ε' and ε") and dielectric modulus (M' and M") were investigated. The XRD spectral data reveals the crystalline nature of pure LiZnVO4 with rhombohedral structure with an average size of 83 nm calculated using the Scherrer’s equation and W-L plot. The interaction between PVDF and LiZnVO4 was approved through the shift in characteristics in some IR bands. The decrease in band gap energies with increasing LiZnVO4 was attributed to the change of density in the localized states within the PVDF matrix. The effect of both frequency and temperature on the AC parameters was also investigated. Both ε' and ε" had their maximum values at low frequencies and decreased as the frequency and temperature increased. The results from XRD and FT-IR were correlated with changes in the dielectric characteristics at the maximum level value of LiZnVO4, suggesting the potential of these materials as basic components for lithium-ion batteries.
Surface deformation of northeastern Taiwan revealed by geomorphic indices
Authors: Yang Chin-Yi , Huang Ting-Wei , Chang Chung-Pai , Hsieh Pei-Shan 
Published: July 2023

AbstractIn northeast Taiwan, many areas are affected by various tectonic forcings. Some areas appear to have a subsidence tendency, whereas others reflect uplift activities on the surface, due to tectonic northward compressive forcing growth and decline. Owing to the presence of widespread mountain areas, limited geodetic surveys in the field have made data scarce in the study area in the past decades. The distribution of the geomorphic indices, which were calculated along the river channels, were used to analyze the activities on a regional scale in this study. The long-term landscape evolution of drainage basins can record topographic changes through the river channels. By calculating the location and drop height of knickpoint in the river longitudinal profile, as well as the spatial distribution of the normalized steepness index ($${K}_{sn}$$Ksn) value, it is possible to comprehensively discuss the perturbations that were caused by possible factors in river channels. Our results from the geomorphic indices synthetically suggest that the river channel of drainage basins is mainly influenced by the perturbations such as geological structures, tectonic activity, various lithologies, potential ruptures. In the study area, tectonic forcing act on a large area from north to south, which is reflected in the long-term incision of the river into the bedrock. Moreover, the potential ruptures on the surface may also induce displacement in the local area.
Asymptotics of Solutions for Periodic Problem for the Korteweg-de Vries Equation with Landau Damping, Pumping and Higher Order Convective Non Linearity
Authors: Juárez-Campos Beatriz , Villela-Aguilar José , Carreño-Bolaños Rafael 
Published: July 2023

AbstractWe study the periodic problem for the Korteweg–de Vries equation with Landau damping, linear pumping and a higher-order convective nonlinearity $$\begin{aligned} \left\{ \begin{array}{c} w_{t}+w_{xxx}-\alpha w_{xx}=\beta w+\lambda w_{x}^{2}w_{xx},\text { }x\in \Omega ,t>0,\\ w(0,x)=\psi \left( x\right) ,\text { }x\in \Omega , \end{array} \right. \end{aligned}$$

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t

+

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=
β
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+
λ

w

x

2

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xx

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∈
Ω
,
t
>
0
,

w

(
0
,
x
)

=
ψ

x

,

x
∈
Ω
,

where, $$\alpha ,\beta >0,$$

α
,
β
>
0
,

$$\lambda \in \mathbb {R},$$

λ
∈
R
,

$$\Omega =\left[ -\pi ,\pi \right] .$$

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=

-
π
,
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.

We assume that the initial data $$\psi \left( x\right) $$

ψ

x

are $$2\pi $$

2
π

- periodic. We prove the global existence of solutions and analyze their large-time asymptotics.
The Future of AI Is in the States: The Case of Autonomous Vehicle Policies
Authors: Mallinson Daniel J. , Azevedo Lauren , Best Eric , Robles Pedro , Wang Jue 
Published: July 2023

AbstractThe myriad applications of artificial intelligence (AI) by the private and public sectors have exploded in the public consciousness in the postpandemic period. However, researchers and businesses have been working on AI technology applications for decades, and in many ways, governments are rushing to catch up. This article presents an argument that the future of AI policy in the United States will be driven in large part by current and future state-level policy experiments. This argument is presented by drawing on scholarship surrounding federalism, regulatory fragmentation, and the effects of fragmentation on business and social equity. The article then presents the case of autonomous vehicle policy in the states to illustrate the degree of current fragmentation and considers the effects of layering new AI policies on top of existing rules surrounding privacy, licensing, and more. Following this consideration of existing research and its application of AI policy, the article presents a research agenda for leveraging state differences to study the effects of AI policy and develop a cohesive framework for governing AI.
The incidence of psychotic disorders in the Republic of Ireland: a systematic review
Authors: Jacinto R. P. , Ding T. , Stafford J. , Baio G. , Kirkbride J. B. 
Published: July 2023

AbstractObjectives:Despite a substantial epidemiological literature on the incidence of psychotic disorders in Ireland, no systematic review has previously been undertaken. Such evidence can help inform understanding of need for psychosis care.Methods:We conducted a prospectively registered systematic review (PROSPERO: CRD42021245891) following PRISMA guidelines. We searched four databases (Medline, PsycInfo, Web of Science, Embase) for papers containing incidence data on non-organic psychotic disorders, in people 16–64 years, published between 1950 and 2021 in the general adult population. We conducted duplicate screening, risk of bias assessments, and extracted data to a standardised template. We undertook a narrative synthesis for each major diagnostic outcome. Random effects meta-analyses were conducted for comparisons with ≥5 incidence rates.Results:Our search yielded 1975 non-duplicate citations, of which 23 met inclusion criteria, containing incidence data ascertained between 1974 and 2016 (median study quality: 5/8; interquartile range: 4–6). Incidence of all psychotic disorders (N = 4 studies) varied from 22.0 (95%CI: 17.3–28.0) in Dublin to 34.1 per 100,000 person-years (95%CI: 31.0–37.5) in Cavan and Monaghan. The pooled incidence of schizophrenia (N = 6 studies, N = 8 settings) was 20.0 per 100,000 person-years, though with imprecision around this estimate (95%CI: 10.6–37.5; I2: 97.6%). Higher rates of most outcomes were observed in men. There was consistent evidence of raised rates in more deprived and fragmented social environments, but no clear pattern by rural-urban status.Conclusions:Patterns of incidence of psychotic disorders in Ireland are broadly consistent with the wider literature from the Global North. Findings could help identify populations at higher risk of psychosis in Ireland.