bluuebunny/crossref_metadata_2025_split huggingface dataset:
2040 greenhouse gas reduction targets and energy transitions in line with the EU Green Deal
Authors: Rodrigues Renato , Pietzcker Robert , Sitarz Joanna , Merfort Anne , Hasse Robin , Hoppe Johanna , Pehl Michaja , Ershad Ahmad Murtaza , Baumstark Lavinia , Luderer Gunnar 
Published: August 2023

AbstractThe European Green Deal aims to guide the European Union towards achieving net-zero greenhouse gas emissions by implementing a comprehensive set of policy initiatives and legislation. While emission reduction targets and policies up to 2030 are mostly implemented, it is of high priority for EU legislation to spell out the further transformation to climate neutrality by defining interim policy targets for 2040. Here we explore, based on an integrated energy-economy-climate model with high sector detail, pathways to achieve climate neutrality in the EU under uncertainty about key energy system developments. Results suggest that emission reductions of 87–91% by 2040 relative to 1990 are consistent with a cost-efficient distribution of mitigation efforts over time, substantially exceeding the 78%-level implied by a linear interpolation between the 2030 and 2050 goals. Additionally, we identify a 5-7-fold upscaling of electricity generation from wind and solar, a 44–50% share of electricity in final energy supply and an upscaling of Carbon Capture and Storage to 120–330 Mt CO2/yr as crucial transformation milestones for 2040.
Toe brachial index and not ankle brachial index is a surrogate to CT angiography in the evaluation of peripheral arterial disease in type 2 diabetes
Authors: Singhania Pankaj , Das Tapas Chandra , Bose Chiranjit , Mondal Asif , Bhattacharjee Rana , Singh Archana , Mukhopadhyay Satinath , Chowdhury Subhankar 
Published: August 2023

Abstract
Background
Non-invasive clinic-based tools for assessing PAD are not without limitations. Therefore, costly tests like Doppler study, CT angiography and MR angiography must be resorted to. Ankle Brachial Index (ABI), commonly used for assessment of PAD, have high false positivity rates in sclerosed, calcified arteries which render them non-compressible. Toe Brachial Index (TBI) can be an alternative, as digital arteries are relatively unaffected by these changes.
Aim
To compare the reliability of ABI and TBI in diagnosing PAD using CT angiography (CTA) as the reference and identify the best surrogate to CTA.
Methods
A total of 350 limbs from 175 adults with T2D were selected. ABI &TBI were measured with an automated vascular Doppler XT 6 ports bilaterally for all subjects. For any subject, the limb with lower ABI and TBI was included for analysis. ABI < 0.9 & TBI < 0.6 were taken as evidence of PAD. CTA showing > 50% narrowing was taken as evidence of PAD.
Results
24% of our study subjects had CTA confirmed PAD. ABI has low sensitivity of 38% (95% CI: 0.21–0.52) compared to TBI being 90% (95% CI: 0.66–0.92). The specificity however was similar. ABI < 0.9 was able to detect CTA confirmed PAD, but ABI > 0.9, including the so-called normal ABI (0.9–1.3) was unable to detect PAD. ROC showed ABI at 1.005 has sensitivity 64.71% (95% CI: 0.48–0.79) and specificity 61.7% (95% CI: 0.53–0.69) and TBI at 0.6 has sensitivity 82.35% (95% CI: 0.66–0.92) & specificity 92% (95% CI:0.87–0.96). Utilizing Cohen’s Kappa, the reliability of ABI with respect to CTA showed fair agreement (K = 0.225, p = 0.001), whereas the reliability of TBI with respect to CTA showed substantial agreement (K = 0.759, p < 0.0001)
Conclusion
ABI < 0.9 detects PAD reliably, but presence of PAD in patients with ABI > 9.0 including the normal of ABI (0.9–1.3) can be confirmed with TBI, which correlated strongly with CTA. TBI is also non-inferior for PAD detection, when ABI < 0.9. TBI and not ABI can be utilized as an apt surrogate to CTA for assessment of PAD in subjects with T2D.
RAD-Seq analysis of wild Japanese garlic (Allium macrostemon Bunge) growing in Japan revealed that this neglected crop was previously actively utilized
Authors: Probowati Wiwit , Koga Shogo , Harada Kentaro , Nagano Yukio , Nagano Atsushi J. , Ishimaru Kanji , Ohshima Kazusato , Fukuda Shinji 
Published: August 2023

Abstract

Wild Japanese garlic (Allium macrostemon Bunge), commonly referred to as "no-biru" in Japan, is a widespread wild onion species found across the country. Despite being deeply entwined in ancient Japanese culture, as evidenced by numerous references in classical literature, it remains an underutilized crop in Japan, contrasting its culinary applications in China and Korea. Determining the origins of its domestic populations and understanding their genetic composition is crucial to highlighting the plant's historical significance in Japan. This study aims to bridge this knowledge gap by examining the genetic diversity of 47 A. macrostemon samples from various regions in Japan using restriction site-associated DNA sequencing (RAD-Seq). Our analysis distinguished unique population structures, dividing the samples into three distinct groups: A, B, and C. Notably, Groups A and B showed clear evidence of bulb propagation, while Group C diverged from this pattern, forming four subgroups C1, C2, C3, and C4. Hybridization between subgroup C1 and either Group A, B, or both, gave rise to subgroups C2, C3, and C4. Thus, Groups A, B, and C1 are posited as the ancestral populations. Additionally, our morphological observations indicated distinct differences among these three groups. Our findings also suggest that human migration may have influenced the plant's distribution, hinting at active usage in the past that later waned, causing its current underutilized status. Gaining insight into the genetic diversity of A. macrostemon has significant implications. It could improve its desirable traits, such as bulb and leaf quality for culinary purposes, potentially triggering a renaissance in its use as a food source in Japan.
Isolation and Structure Elucidation of Bis(2-ethylhexyl) terephthalate from barks of Acacia xanthophloea
Authors: Michael Cheloti , Phanice Wangila , Ambrose Kiprop , Arthur Onyuka , Solomon Derese , Mukavi Justus , Ingrid Wekesa , Emmanuel Kariuki , Gladys Mugo , Martin Murimi 
Published: August 2023

Abstract
A common and native tree of Eastern and Southern Africa, Acacia xanthophloea is a species of tropical plants and a member of the Fabaceae family.Although A. xanthophloea is known as a source of tannins, very little is known about its phytochemistry. In this context, the main objective of this work was to isolate and characterize the structures of secondary metabolites found in the bark of this plant. Substantial amounts of bis(2-ethylhexyl) terephthalate [DEHT/ dioctyl terephthalate (DOTP)] were isolated in a fraction of the bark extract while undertaking the isolation of phytochemicals from A. xanthophloea barks. The structure of this compound was confirmed by NMR, and mass spectroscopic data. DEHT is a terephthalic acid ester, the main plasticizer that is used to confer elasticity and flexibility to various fiber and plastic products. To the best of our knowledge, this is the first time DEHT has been isolated from the barks of A. xanthophloea. This study contributes to the growing evidence of plasticizers in our food and drug sources.
Effect of Content and Language Integrated Learning/ CLIL/ on EFL students’ reading motivation and comprehension in Ethiopia
Authors: Etefa Fanta , Yigzaw Abiy , Shifere Kassie , Tezera Melku 
Published: August 2023

Abstract

The purpose of this study was to examine the effect of content and language integrated learning/ CLIL/ on EFL students’ reading comprehension and reading motivation in Ethiopia. To this end, a quasi-experimental pretest –posttest design was used. Thus, sixty- nine EFL learners from two randomly selected sections of grade nine were used as the study’s participants. The sections were then randomly assigned as control (n=35) and experimental (n=34) groups. To collect data, a reading motivation questionnaire and reading comprehension test were utilized. Pretests were first given to both groups to examine if there were mean differences between the two groups. Then, treatment on CLIL reading strategies was given to the experimental group. Thenceforth, posttests were given to both groups. Data were analyzed using descriptive statistics, namely mean, standard deviation and inferential statistics of independent samples t-test, paired t-test, Mann-Whitney U Test and Wilcoxon Signed Rank Test. The findings from data analysis revealed that CLIL had a significant positive effect on students’ reading comprehension and motivation. Moreover, the findings signposted that CLIL approach needed to be incorporated in EFL teaching materials in Ethiopia
An efficient and reliable protocol on in vitro propagation of ‘Colt’ (Prunus avium F 299/2 x Prunus pseudocerasus Lind) rootstock of cherry
Authors: Mir M. A. , Manzoor Ikra , Kashani Syed Zainab , Attia Houneida , Bhat Momin Showkat , Abidi Ishfaq. A. , Alamer Khalid H. , Dar Showket Ahmad , Lone Showkat A , Iesa Mohamed A. M. , Al-Qarni Maha , Fekry Waleed M.E. , Sultan Rania Mohammad Sabri , Ainusairi Ghalia S.H. , Zoubi Omar Mahmoud Al , Alharbi Basmah M. , Moqbel Fahmi S , Youssef Rawa M 
Published: August 2023

Abstract
Background The 'Colt' is a triploid hybrid of P. avium and P. pseudocerasusL. grown as a cherry rootstock because of its resistance to cherry stem pitting (a debilitating virus disease), Phytophthora root rot, bacterial canker, and gopher damage.
ResultsThe current study was carried out using two types of explants: forced (F1) and unforced (F2) and five types of sterilants were used to sterilize explants: 10% sodium hypochlorite (NaOCl) for 10 minutes (S1), 0.1% mercuric chloride (HgCl2) for 5 minutes (S2), ethyl alcohol for 10 seconds (S3), (S1) + (S3) & (S2) + (S3) for sterilization. During culture establishment, six growth regulator regimes viz., BA (Benzyl adenine) (0.20), (0.40) & (0.60) and BA+IBA (Indole-3-butyric acid) (0.20+0.01), (0.40+0.01), and (0.60+0.01) mg/l, two media i.e., MS (Murashige and Skoog, 1962)& WPM (Woody Plant Medium)& two types of explants viz., forced (F1) & unforced shoot tips(F2) were utilized. During shoot proliferation, MS & WPM culture medium with growth regulators viz., BA (0.20), (0.40) & (0.60), BA+IBA (0.20+0.01), (0.40+0.01) and (0.60+0.01) mg/l were used respectively. During rhizogenesis using different media (MS & WPM) with various levels of IBA (0.50), (1.00) (1.50), and (2.00) mg/l, respectively were used. The superior rooted plants were hardened in sand & cocopeat respectively.
Conclusion In this experiment, maximum culture asepsis (%) obtained in unforced shoot tips(F2) with (S5),maximum explant survival (%) in forced shoot tips (F1) with (S4), and highest establishment (%) with MS medium, BA (0.6) mg/l & in forced shoot tips (F1). Significantly higher shoot proliferation is obtained with MS medium with BA (0.6) mg/l , maximum shoot number & length in WPM medium with BA (0.2) mg/l. A significantly higher rooting percentage was obtained in MS medium with IBA (1.00) mg/l with maximum ex vitro survival (%) in cocopeat.
Absolute and non-invasive determination of the electron bunch length in a Free Electron Laser using a Bunch Compressor Monitor
Authors: Orlandi Gian Luca 
Published: August 2023

Abstract
In a linac driven Free Electron Laser (FEL), the shot-to-shot and non-invasive monitoring of the electron bunch length is normally ensured by Bunch Compressor Monitors (BCMs). The bunch-length dependent signal of a BCM results from the detection and integration - over a given frequency band - of the temporal coherent enhancement of the radiation spectral energy emitted by the electron beam while experiencing a longitudinal compression. In this work, we present a method that permits to express the relative variation of the bunch length as a function of the relative statistical fluctuations of the BCM and charge signals. Furthermore, in the case of a BCM equipped with two detectors simultaneously operating in two distinct wavelength bands, the method permits an absolute determination of the electron bunch length. The proposed method is beneficial to a FEL since it permits to tune the machine compression feedback with respect to the absolute measurement of the bunch length instead of a bunch-length dependent signal. In a CW-superconducting-linac driven FEL, it can offer the precious opportunity to implement a fully non-invasive and absolute diagnostics of the bunch length.
A New Ensemble Method for Brain Tumor Segmentation
Authors: Laouali Souleymane Mahaman , Chebbah Mouna , Nakouri Haïfa 
Published: August 2023

Abstract
In the medical field, Magnetic resonance image (MRI) brain tumor segmentation
is highly crucial and important. Tumor segmentation can
help in diagnosis and prognosis, overall growth predictions, Tumor density
measures, and care treatment plans needed for patients. However,
this task is extremely challenging due to low contrast, noise in medical
images, and to the voluminous size of data. This work focuses on
improving medical image semantic segmentation using a time-efficient
ensemble learning approach. We propose a novel ensemble deep approach
using a Convolutional Neural Network and three Autoencoders to extract
relevant features from brain MRIs, reduce dimensionality, then apply
supervised learning for pixel-by-pixel binary classification to achieve
tumor segmentation. Experiments show promising results with our model
achieving a Dice Similarity Coefficient of 88.63%, a Jaccard Similarity
Index of 79.58% and a Recall of 84.34%, thus demonstrating
the model’s ability to identify the tumor’s pixels with precision while
consuming fewer resources. Therefore, the segmentation performance
is sufficiently addressed in terms of accuracy, reliability and speed.
Exergoeconomic analysis and optimization of wind power hybrid energy storage system
Authors: Wen Caifeng , Lv Yalin , Du Qian , Zhang Boxin , Lian Xuhui , Wang Qiang 
Published: August 2023

Abstract
Taking the thermal-electric hybrid energy storage wind power system with the effective combination of thermal energy storage and battery energy storage as the research object, the exergoeconomic characteristics of the system are studied experimentally. Firstly, RSM is used to optimize the power quality and exergoeconomic characteristics of the system, and the optimal operating conditions are obtained. Then, an optimization strategy is proposed based on MOPSO algorithm to explore the effective ways to improve the exergetic efficiency of each subsystem and reduce the system exergy loss and system exergetic cost. The results show that the exergo-economics can effectively evaluate the generation-energy storage characteristics of the new wind power system of ' wind power + energy storage '. It is confirmed that the proposed optimization strategy and algorithm can avoid the situation of low η2, η3 and η when λ is small. When λ is large, the unit exergy cost and current harmonic distortion are further reduced, and the power quality and system exergy efficiency are improved while the unit exergy cost is reduced, so as to realize the optimal configuration of the thermal-electric hybrid energy storage wind power system.
DeepSearch: A deep learning based document retrieval system
Authors: Malik M. Shoaib , Klakow Dietrich , Waltemath Dagmar 
Published: August 2023

Abstract
Deep learning has enabled machines to be used for many tasks, including computer vision, image recognition, natural language processing, self-driving cars, and predicting the contingencies of certain business transactions. Effective application of deep learning techniques can help develop intelligent applications. Many web-based tools get their information from generic search engines such as Google but also specialized search engines such as PubMed (for retrieving information on biomedical publications). In this study, we evaluate the performance of different deep learning architectures for the task of document retrieval. Our goal was to identify the optimal architecture for the document retrieval task. We therefore compare the deep architecture of feed-forward neural networks with recurrent neural networks, in particular the long short-term memory neural networks. We observe that the local context is not sufficient as it does not provide reliable predictions, which are, however, provided by long distance dependencies where long short-term memory neural networks are used. We first describe the algorithms used for our evaluation and then compare their performance. Our dataset contained two publicly available document sets from the 20-Newsgroup and BBC, respectively.
One-pot, degradable, silica nanocarriers with encapsulated oligonucleotides for mitochondrial specific delivery
Authors: Trayford Chloe , Wilhalm Alissa , Habibovic Pamela , Smeets Hubert , Tienen Florence , Rijt Sabine van 
Published: August 2023

Abstract
Mutations in nuclear and mitochondrial genes are responsible for severe chronic disorders such as mitochondrial myopathies (MM). Gene therapy using antisense oligonucleotides is a promising strategy to treat mitochondrial DNA (mtDNA) diseases by blocking the replication of the mutated mtDNA. However, transport vehicles are needed for intracellular, mitochondria-specific transport of oligonucleotides. Nanoparticle (NP) based vectors such as large pore mesoporous silica nanoparticles (LP) often rely on surface complexation of oligonucleotides exposing them to nucleases and limiting mitochondria targeting and controlled release ability. In this work, stable, fluorescent, hollow silica nanoparticles (HSN) that encapsulate and protect oligonucleotides in the hollow core were synthesized by a facile one-pot procedure. Our HSN were dual-doped with rhodamine B isothiocyanate (RITC) and bis[3-(triethoxysilyl)propyl]tetrasulfide (BTES) to enable cell tracing, intracellular-specific degradation and controlled oligonucleotide release. We also synthesized LP as a benchmark to compare the oligonucleotide loading and release efficacy of our HSN. Mitochondria targeting was enabled by NP functionalization with TPP and, for the first time, MITO-porter. HSN exhibited high oligonucleotide incorporation ratios and release dependent on intracellular degradation. Further, MITO-porter capping of our NP enabled delayed, glutathione (GSH) responsive oligonucleotide release and mitochondria targeting at the same efficiency as TPP functionalized NP. Overall, our NP are promising vectors for anti-gene therapy of mtDNA disease as well as many other monogenic disorders worldwide.
Pollution by presumed domestic sewage in storm drainage in separated sewer areas
Authors: Ozaki Noriatsu , Kindaichi Tomonori , Ohashi Akiyoshi 
Published: August 2023

Abstract
The deteriorating state of infrastructure poses a threat to developed countries, emphasizing the need for the development of effective management and maintenance techniques. Among various concerns, the leakage of aged domestic sewer pipelines has become a significant issue. In this study, we measured hydrophobic organic pollutants such as PAHs, fragrance substances, and caffeine in standing water samples collected from storm drains in five different urban areas that have separate sewer systems. The pollution levels of PAHs did not differ significantly between the districts, while notable differences were observed in fragrance substances and caffeine. Their pollution levels tended to increase with the age of the sewer systems, with caffeine concentrations being over two orders of magnitude higher in districts with sewage systems aged over 40 years compared to those with systems just ten years old. Furthermore, from a comparison of different older storm discharge areas, different high-concentration patterns for between caffeine and musk fragrance substances, possibly reflecting different leakage situations.
Logistics performance, transaction cost economics, trade liberalization, and agricultural food worldwide
Authors: Shikur Zewdie Habte , Bahta Yonas 
Published: August 2023

Abstract

The purpose of this study is to examine the relationship between multi-explanatory variables and food trade in a global context to fill a research gap using System General Method of Moments (GMM) framework analysis that, to the best of our knowledge, has not been applied regarding this issue, our aim is to contribute to the existing literature. The study provides additional insight by explaining the link between transaction cost economics, logistics performance, and food trade, which remains unknown. Therefore, the paper provides further insights compared to the earlier work by shedding light on how various dimensions of logistics performance determine food export and import in light of the current situation of food shortages. The model results indicated that trade liberalization has a negative impact on food exports and imports. The adoption of chemical fertilizers has a significant and negative impact on food exports but is insignificant on food imports due to a significant shift in consumer demand from inorganic to organic foods globally. The model's findings show that logistics services, shipments, customs and clearance, and infrastructure are all significant and positive drivers of agricultural food exports and imports except for timeliness and tracking and tracing. The size of agricultural land is found to be positively and significantly related to the food trade. Therefore, countries should integrate logistics performance enhancement, transaction cost economics, and an organic production system into their policy formulation and implementation to increase food trade. A framework makes the countries with low transaction costs more likely to trade food with other low transaction cost countries and vice versa for high transaction costs.
Deep Convolutional Architectures for Extrapolative Forecasts in Time-dependent Flow Problems
Authors: Bhatt Pratyush , Kumar Yash , Soulaïmani Azzeddine 
Published: August 2023

Abstract
Physical systems whose dynamics are governed by partial differential equations (PDEs) find numerous applications in science and engineering. The process of obtaining the solution from such PDEs may be computationally expensive for large-scale and parameterized problems. In this work, deep learning techniques developed especially for time-series forecasts, such as LSTM and TCN, or for spatial-feature extraction such as CNN, are employed to model the system dynamics for advection-dominated problems. This paper proposes a Convolutional Autoencoder(CAE) model for compression and a CNN future-step predictor for forecasting. These models take as input a sequence of high-fidelity vector solutions for consecutive time steps obtained from the PDEs and forecast the solutions for the subsequent time steps using auto-regression; thereby reducing the computation time and power needed to obtain such high-fidelity solutions. Non-intrusive reduced-order modeling techniques such as deep auto-encoder networks are utilized to compress the high-fidelity snapshots before feeding them as input to the forecasting models in order to reduce the complexity and the required computations in the online and offline stages. The models are tested on numerical benchmarks (1D Burgers’ equation and Stoker’s dam-break problem) to assess the long-term prediction accuracy, even outside the training domain (i.e. extrapolation). The most accurate model is then used to model a hypothetical dam break in a river with complex 2D bathymetry. The proposed CNN future-step predictor revealed much more accurate forecasting than LSTM and TCN in the considered spatiotemporal problems.