bluuebunny/crossref_metadata_2025_split huggingface dataset:
An analysis of environment effect on ethanol blends with plastic fuel and blend optimization using a full factorial design
Authors: Padmanabhan S. , Kumar T. Vinod , Giridharan K. , Stalin B. , Nagaprasad N. , Jule Leta Tesfaye , Ramaswamy Krishnaraj 
Published: December 2022

AbstractThere is a growing amount of plastic waste that needs to be properly disposed of in order to protect the environment from the negative effects of increasing reliance on plastic products. Recent interest has focused on chemical recycling as a means of reducing plastic's negative environmental effects. Converting waste plastics into basic petrochemicals allows them to serve as hydrocarbon feedstock or fuel oil through pyrolysis operations. Scientists have taken a keen interest in the production of bioethanol from renewable feedstocks due to its potential as a source of energy and alternative fuel. Due to its beneficial effects on the environment, ethanol has emerged as a promising biofuel. In this paper, energy recovered from low-density polyethylene and high-density polyethylene waste was converted into an alternative plastic fuel and evaluated for its environmental impact with the blending of ethanol in a diesel engine. Ternary fuel blends with 20%, 30%, and 40% waste plastic fuel and 10%, 15%, and 20% ethanol with standard diesel were tested. The study found that blending 10% ethanol with 20% plastic fuel decreased fuel consumption by around 7.9% compared to base diesel. Carbon monoxide emissions are reduced by about 10.2%, and hydrocarbon emissions are reduced by about 13.43% when using the same ternary blend. The optimum values of fuel consumption and emissions were obtained by full factorial design for a ternary fuel blend of 10% ethanol and 20% plastic fuel at the full load condition.
Relationship between quadriceps femoris muscle architecture and muscle strength and physical function in older adults with heart failure with preserved ejection fraction
Authors: Fuentes-Abolafio Iván J. , Bernal-López M. Rosa , Gómez-Huelgas Ricardo , Ricci Michele , Cuesta-Vargas Antonio I. , Pérez-Belmonte Luis M. 
Published: December 2022

AbstractHeart failure (HF)-related factors potentially lead to sarcopenia. Ultrasound (US) assessment has all the advantages of being used in clinical practice to assess muscle architecture. This study aimed to assess the relationship between the quadriceps femoris (QF) muscle architecture with the gender, age, body mass index (BMI), muscle strength and physical function in older adults with HF with preserved ejection fraction (HFpEF) as well as to assess the difference in these relationships between the two genders. Patients 70 years and older with HFpEF were included. The gender, age and BMI were collected. The QF muscle thickness, the QF muscle echo-intensity, the subcutaneous fat tissue thickness (FT) and the subcutaneous fat tissue echo-intensity were assessed by the US. The six-minute walk test, the short physical performance battery (SPPB), the timed up and go test (TUG), and the gait speed test (UGS) were used to assess physical function. The five-repetitions sit-to-stand test (5-STS) was performed to assess muscle strength. Bivariant Pearson correlations and subsequent multivariate linear regression analysis were conducted. Seventy older adults with HFpEF [81.00 (5.97) years] were recruited. The FT showed a correlation between poor and moderate muscle strength and physical function in women with HFpEF. The FT explained 24.5% of the 5-STS variance, 32.4% of the SPPB variance, 31.5% of the TUG variance, 28.6% of the UGS variance, and 21.4% of the FGS variance in women. The US assessment could allow clinicians to assess muscle architecture biomarkers related to muscle strength and physical function in older adults with HFpEF.Trial registration NCT03909919. April 10, 2019. Retrospectively registered.
Temporal judgments of actions following unilateral brain damage
Authors: Pacella Valentina , Scandola M. , Bà M. , Smania N. , Beccherle M. , Rossato E. , Volpe D. , Moro Valentina 
Published: December 2022

AbstractSense of time is a complex construct, and its neural correlates remain to date in most part unknown. To complicate the frame, physical attributes of the stimulus, such as its intensity or movement, influence temporal perception. Although previous studies have shown that time perception can be compromised after a brain lesion, the evidence on the role of the left and right hemispheres are meager. In two experiments, the study explores the ability of temporal estimation of multi-second actions and non-biological movements in 33 patients suffering from unilateral brain lesion. Furthermore, the modulatory role of induced embodiment processes is investigated. The results reveal a joint contribution of the two hemispheres depending not only on different durations but also on the presence of actions. Indeed, the left hemisphere damaged patients find it difficult to estimate 4500 ms or longer durations, while the right hemisphere damaged patients fail in 3000 ms durations. Furthermore, the former fail when a biological action is shown, while the latter fail in non-biological movement. Embodiment processes have a modulatory effect only after right hemisphere lesions. Among neuropsychological variables, only spatial neglect influences estimation of non-biological movement.
A potential role for SARS-CoV-2 small viral RNAs in targeting host microRNAs and modulating gene expression
Authors: Neeb Zachary T. , Ritter Alexander J. , Chauhan Lokendra V. , Katzman Sol , Lipkin W. Ian , Mishra Nischay , Sanford Jeremy R. 
Published: December 2022

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease (COVID-19) in humans, with symptoms ranging from mild to severe, including fatality. The molecular mechanisms surrounding the effects of viral infection on the host RNA machinery remain poorly characterized. We used a comparative transcriptomics approach to investigate the effects of SARS-CoV-2 infection on the host mRNA and sRNA expression machinery in a human lung epithelial cell line (Calu-3) and an African green monkey kidney cell line (Vero-E6). Upon infection, we observed global changes in host gene expression and differential expression of dozens of host miRNAs, many with known links to viral infection and immune response. Additionally, we discovered an expanded landscape of more than a hundred SARS-CoV-2-derived small viral RNAs (svRNAs) predicted to interact with differentially expressed host mRNAs and miRNAs. svRNAs are derived from distinct regions of the viral genome and sequence signatures suggest they are produced by a non-canonical biogenesis pathway. 52 of the 67 svRNAs identified in Calu-3 cells are predicted to interact with differentially expressed miRNAs, with many svRNAs having multiple targets. Accordingly, we speculate that these svRNAs may play a role in SARS-CoV-2 propagation by modulating post-transcriptional gene regulation, and that methods for antagonizing them may have therapeutic value.
Multi-fractal detrended cross-correlation heatmaps for time series analysis
Authors: de Melo Barros Junior Paulo Roberto , Bunge Kianny Lopes , Serravalle Reis Rodrigues Vitor Hugo , Ferreira Santiago Michell Thompson , dos Santos Marinho Euler Bentes , Lima de Jesus Silva Jose Luis 
Published: December 2022

AbstractComplex systems in biology, climatology, medicine, and economy hold emergent properties such as non-linearity, adaptation, and self-organization. These emergent attributes can derive from large-scale relationships, connections, and interactive behavior despite not being apparent from their isolated components. It is possible to better comprehend complex systems by analyzing cross-correlations between time series. However, the accumulation of non-linear processes induces multiscale structures, therefore, a spectrum of power-law exponents (the fractal dimension) and distinct cyclical patterns. We propose the Multifractal detrended cross-correlation heatmaps (MF-DCCHM) based on the DCCA cross-correlation coefficients with sliding boxes, a systematic approach capable of mapping the relationships between fluctuations of signals on different scales and regimes. The MF-DCCHM uses the integrated series of magnitudes, sliding boxes with sizes of up to 5% of the entire series, and an average of DCCA coefficients on top of the heatmaps for the local analysis. The heatmaps have shown the same cyclical frequencies from the spectral analysis across different multifractal regimes. Our dataset is composed of sales and inventory from the Brazilian automotive sector and macroeconomic descriptors, namely the Gross Domestic Product (GDP) per capita, Nominal Exchange Rate (NER), and the Nominal Interest Rate (NIR) from the Central Bank of Brazil. Our results indicate cross-correlated patterns that can be directly compared with the power-law spectra for multiple regimes. We have also identified cyclical patterns of high intensities that coincide with the Brazilian presidential elections. The MF-DCCHM uncovers non-explicit cyclic patterns, quantifies the relations of two non-stationary signals (noise effect removed), and has outstanding potential for mapping cross-regime patterns in multiple domains.
Global habitat suitability modeling reveals insufficient habitat protection for mangrove crabs
Authors: Yousefi Masoud , Naderloo Reza 
Published: December 2022

AbstractMangrove crabs are important components of mangrove forests however their large scale habitat suitability and conservation received little attention. The Metopograpsus thukuhar/cannicci species complex is a mangrove dwelling species occurs in the Indo-Pacific mangrove forests. Since identifying the complex suitable habitat is critical for its conservation, we modeled global habitat suitability of the complex within marine biogeographic realms and estimated representation of the complex suitable habitats within marine protected areas. We found that the complex’ largest and smallest suitable ranges are located in Central Indo-Pacific and Temperate Southern Africa realms, respectively. Only 12.5% of the complex suitable habitat is protected. The highest proportion of the complex’ protected suitable habitat (22.9%) is located in Western Indo-Pacific realm while the lowest proportion of the complex’ protected suitable habitat (1.38%) is located in Central Indo-Pacific realm. Suitable unprotected habitats of the complex identified in this study have high priority for conservation and should be included in marine protected areas to ensure species conservation. Our results show that species distribution models are practical tools to study marine species distribution across large spatial scales and help marine conservation planning.
Vagus nerve stimulation attenuates acute kidney injury induced by hepatic ischemia/reperfusion injury in rats
Authors: Deng Simin , Zhang Yifeng , Xin Ying , Hu Xinqun 
Published: December 2022

AbstractHepatic ischemia/reperfusion (I/R) injury, caused by limited blood supply and subsequent blood supply, is a causative factor resulting in morbidity and mortality during liver transplantation and liver resection. Hepatic I/R injury frequently contributes to remote organ injury, such as kidney, lung, and heart. It has been demonstrated that vagus nerve stimulation (VNS) is effective in remote organ injury after I/R injury. Here, our aim is to investigate the potential action of VNS on hepatic I/R injury-induced acute kidney injury (AKI) and explore its underlying mechanisms. To test this hypothesis, male Sprague–Dawley rats were randomly assigned into three experimental groups: Sham group (sham operation, n = 6); I/R group (hepatic I/R with sham VNS, n = 6); and VNS group (hepatic I/R with VNS, n = 6). VNS was performed during the entire hepatic I/R process. Our results showed that throughout the hepatic I/R process, VNS significantly regulated the expression levels of various iconic factors and greatly enhanced the protein expression levels of nuclear factor erythroid 2-related factor 2 (Nrf2) and hemeoxygenase-1 (HO-1) in the kidneys. These findings suggested that VNS may ameliorate hepatic I/R injury-induced AKI by suppressing inflammation, oxidative stress, and apoptosis probably through activating the Nrf2/HO-1 signaling pathway.
First-principles structural, elastic and optoelectronics study of sodium niobate and tantalate perovskites
Authors: Khattak Shaukat Ali , Wabaidur Saikh Mohammad , Islam Md Ataul , Husain Mudasser , Ullah Irfan , Zulfiqar Syed , Rooh Gul , Rahman Nasir , Khan Muhammad Salman , Khan Gulzar , Khan Tahirzeb , Ghlamallah Benabdellah 
Published: December 2022

AbstractThe intensified quest for efficient materials drives us to study the alkali (Na)-based niobate (NaNbO3) and tantalate (NaTaO3) perovskites while exploiting the first-principles approach based on density functional theory, coded within WIEN2K. While using the Birch Murnaghan fit, we find these materials to be stable structurally. Similarly, the ab-initio molecular dynamics simulations (AIMD) at room temperature reveals that the compounds exhibit no structural distortion and are stable at room temperature. By using the recommended modified Becke–Johnson potential, we determine the electronic characteristics of the present materials providing insight into their nature: they are revealed to be indirect semiconductors with the calculated bandgaps of 2.5 and 3.8 eV for NaNbO3 and NaTaO3, respectively. We also determine the total and partial density of states for both materials and the results obtained for the bandgap energies of these materials are consistent with those determined by the band structure. We find that both compounds exhibit transparency to the striking photon at low energy and demonstrate absorption and optical conduction in the UV region. The elastic study shows that these compounds are mechanically stable, whereas NaNbO3 exhibits stronger ability to withstand compressive as well as shear stresses and resists change in shape while NaTaO3 demonstrates weaker ability to resist change in volume. We also find that none of the compound is perfectly isotropic and NaNbO3 and NaTaO3 are ductile and brittle in nature, respectively. By studying the optical properties of these materials, we infer that they are promising candidates for applications in optoelectronic devices. We believe that this report will invoke the experimental studies for further investigation.
Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes
Authors: Hamzehali Hamideh , Lotfi Shahram , Ahmadi Shahin , Kumar Parvin 
Published: December 2022

AbstractChronic myelogenous leukemia (CML) which is resulted from the BCR-ABL tyrosine kinase (TK) chimeric oncoprotein, is a malignant clonal disorder of hematopoietic stem cells. Imatinib is used as an inhibitor of BCR-ABL TK in the treatment of CML patients. The main object of the present manuscript is focused on constructing quantitative activity relationships (QSARs) models for the prediction of inhibition potencies of a large series of imatinib derivatives against BCR-ABL TK. Herren, the inbuilt Monte Carlo algorithm of CORAL software is employed to develop QSAR models. The SMILES notations of chemical structures are used to compute the descriptor of correlation weights (CWs). QSAR models are established using the balance of correlation method with the index of ideality of correlation (IIC). The data set of 306 molecules is randomly divided into three splits. In QSAR modeling, the numerical value of R2, Q2, and IIC for the validation set of splits 1 to 3 are in the range of 0.7180–0.7755, 0.6891–0.7561, and 0.4431–0.8611 respectively. The numerical result of $${CR}_{p}^{2}$$

CR

p

2

> 0.5 for all three constructed models in the Y-randomization test validate the reliability of established models. The promoters of increase/decrease for pIC50 are recognized and used for the mechanistic interpretation of structural attributes.
Pain estimation with integrating global‐wise and region‐wise convolutional networks
Authors: Huang Dong , Xia Zhaoqiang , Li Lei , Ma Yupeng 
Published: December 2022

AbstractPain is a common phenomenon in clinical patients, which indicates patients are suffering from uncomfortable conditions for necessary treatments. So the assessment of pain status becomes a significant task in current medical institutions. Of late, various conventional hand‐crafted or deep learning methods on face images are presented to estimate pain intensity automatically. However, these approaches usually feed the whole face into the automatic estimation system and explore little information on the interdependencies of related regions during the formation of pain expression. In this paper, a hierarchical deep network (HDN) involving regional and holistic information simultaneously is proposed via two scale branches. In HDN, a region‐wise branch is designed to extract features from pain related regions of face images while a global‐wise branch explores the interdependencies of pain related regions. Besides, in global‐wise branch, a multi‐task learning method is employed to detect action units while estimating pain intensity. Finally, the pain estimation outputs of two branches are fused in a decision level. On current pain estimation benchmarks, it is empirically shown that the proposed HDN outperforms the existing methods and the essential components in HDN have key influences on final prediction.
Image‐based fall detection in bus compartment scene
Authors: Zhang Xiaoping , Ji Jiahui , Wang Li , He Zhonghe , Liu Shida 
Published: December 2022

AbstractBus, as an important means of public transportation, has always received attention for its safety. When an emergency occurs, fall behaviour is one of representative features to help alarm. However, compared with other open and fixed scenes, the bus compartment has its own characteristics, such as crowded, closed, in moving, and so on. Considering the problems of people blocked as well as light changes, this paper proposes a new image‐based fall detection method in bus compartment scene, which can be divided into three parts: (1) Human detection, where object detection and pose estimation algorithms are combined, and then both global and local human features can be obtained; (2) fall discrimination, where both of the fall discrimination conditions and fall discrimination network are designed; (3) alert, where an alarm strategy is designed. Experiments are done in a real bus, and the Nvidia Jetson Xavier NX module is used to analyse the videos and images. Results finally show that the proposed fall detection method in bus compartment scenes can achieve 90% accuracy.
Energy management and harmonic compensation of micro‐grids via multi‐agent systems based on decentralized control architecture
Authors: Salehirad Mohammadreza , Mollaie Emamzadeh Mohammad 
Published: December 2022

AbstractHere, a new energy management strategy based on a multi‐agent structure is presented by introducing hybrid control of AC micro‐grid (MG), where current harmonics compensation is also considered. This energy management strategy is based on Mealy machine in a multi‐agent system (MAS), which is implemented by generating coordination signals and sending them to the renewable energy sources (RES). In RES, maximum power point tracking (MPPT) or reverse of Hill‐climbing (RHC) is used based on these received coordination signals to limit the exchange power between the MG and the grid. Also, the multi‐agent structure of shunt active power filters (SAPFs) and passive filters have been studied in power MGs. The comparison of MG current harmonic compensation by these filters by fast Fourier transform (FFT) algorithm has been investigated in the proposed network. The simulation results show that the proposed energy management system (EMS) with proper management of MG different agents has been able to have a suitable performance for hybrid distributed generation (DG) systems. Also, the SAPF with better and more appropriate harmonic compensation than the SC‐RC‐LCL passive filter can eliminate the harmonic pollution of MG and be used with high performance in hybrid DG systems.
White Paper – Verbesserung der Versorgungs- und
Behandlungsangebote für Menschen mit Sepsis- und
Infektionsfolgen
Authors: Fleischmann-Struzek Carolin , Rose Norman , Born Sebastian , Freytag Antje , Ditscheid Bianka , Storch Josephine , Schettler Anna , Schlattmann Peter , Wedekind Lisa , Pletz Mathias W. , Sänger Sylvia , Brunsmann Frank , Oehmichen Frank , Apfelbacher Christian , Drewitz Karl-Philipp , Piedmont Silke , Denke Claudia , Vollmar Horst C. , Schmidt Konrad , Landgraf Irmgard , Bodechtel Ulf , Trumann Arne , Hecker Ruth , Reinhart Konrad , Hartog Christiane S. 
Published: December 2022

ZusammenfassungHunderttausende Menschen mit Sepsis- und Infektionsfolgen werden derzeit in
Deutschland nicht optimal versorgt. Dieses White Paper stellt Maßnahmen
zur Verbesserung der Versorgung vor, die von einer multidisziplinären
Expertengruppe im Rahmen des Innovationsfonds-Projektes SEPFROK erarbeitet
wurden. Eine optimale Versorgung beruht auf 4 Säulen: 1. der
sektorenübergreifenden Erfassung der Folgen und einem strukturierten
Entlass- und Überleitungsmanagement, 2. einem gezielten Angebot von
interdisziplinärer Rehabilitation- und Nachsorge mit struktureller
Unterstützung, 3. der Stärkung der spezifischen
Gesundheitskompetenz von Betroffenen und Angehörigen und 4. der
Intensivierung der Forschung zu Ursachen, Prävention und Therapie der
Folgen. Hierfür müssen entsprechende
sektorenübergreifende Versorgungsstrukturen und sozialrechtliche
Rahmenbedingungen geschaffen werden.
Craniotomy or Craniectomy for Acute Subdural Hematoma? Difference in Patient Characteristics and Outcomes at a Tertiary Care Hospital
Authors: Anis Saad Bin , Khan Saad Akhtar , Mitha Rida , Shamim Muhammad Shahzad 
Published: December 2022

Abstract
Objective This article compares the outcomes of patients with traumatic acute subdural hemorrhage (SDH) managed either with craniotomy (CO) or with decompressive craniectomy (DC).
Methods In this single-center, retrospective analysis we included all adult patients with acute traumatic SDH who were treated either using CO or DC. Sixteen-year hospital data was reviewed for patient demographics, injury details, and hospital course. Outcomes were noted in terms of intraoperative blood loss, intensive care unit stay, need for tracheostomy, post-surgery Glasgow Coma Score (GCS; calculated immediately after surgery), delayed GCS (DGCS; calculated 1 week after surgery), and delayed Glasgow Outcome Score (DGOS) after 6 months of surgery. Postoperative complications were noted during hospital stay, while mortality was noted within 6 months of surgery for each patient.
Results Patients who underwent DC were younger (mean age 34.4 ± 16.8 years vs. 42.4 ± 19.9 years in the CO group) (p = 0.006). Patients who underwent DC also had worst degree of traumatic brain injury as per Marshall grade (62.4% patients with Marshall grade 4 in the DC group vs. only 41.2% patients in the CO group) (p = 0.037). Mean size of hematoma was 23.8 ± 24.6 mm in the DC group versus 11.3 ± 8.2 mm in the CO group (p = 0.001). Mean postop GCS was lower in the DC group; 8.0 ± 4 versus 10.8 ± 4 in the CO group (p < 0.001). However, there was no significant difference in DGCS and DGOS between the DC and CO groups (p = 0.76 and 0.90, respectively). Mortality rate was 24 (30.8%) in the DC group versus 18 (20.7%) in the CO group (p = 0.14).
Conclusion The patients who underwent DC were younger, had larger size hematoma, and poor Marshall grade. We did not find any significant difference in the outcomes of CO and DC for management of subdural hematoma.