bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the impact of novel ionic liquid functionalized graphene on the mechanical properties and thermal conductivity of LLDPE composites
Authors: Zhang Jinzhuo , Wang Yijie , Long Jiapeng , Liang Bing 
Published: June 2024

AbstractDue to its high thermal conductivity, graphene finds extensive application in thermal composite materials. However, akin to polymer composites containing other fillers, the thermal resistance at the interface between graphene and the polymer matrix substantially impedes heat conduction. Thus, functionalizing graphene becomes imperative to enhance its dispersibility in polymers. In this study, we synthesized the imidazolyl ionic liquid 1‐methyl‐3‐triethoxysilpropyl imidazole chloride ([MTESiPIM]Cl). Ionic liquid complexes supported by graphene (G) were synthesized via a simple ultrasonic stripping method by combining electrochemical graphene (G) with [MTESiPIM]Cl (Si‐IL@G). The Si‐IL@G/LLDPE composite was formed by blending Si‐IL@G into the linear low‐density polyethylene (LLDPE) matrix using a melt blending technique. Upon adding 5% Si‐IL@G, the tensile strength and bending modulus of Si‐IL@G/LLDPE composite reached 13.5 MPa and 348.2 MPa, respectively, marking an increase of 20.67% and 57.79% over pure LLDPE. The Si‐IL@G/LLDPE composite exhibited a thermal conductivity of 0.49 W·m−1·K−1, 96.0% higher than that of pure LLDPE. Given its outstanding thermal conductivity and mechanical properties, Si‐IL@G holds great potential in producing composites with high thermal conductivity.Highlights
An ionic liquid with siloxanyl groups was synthesized using microwave assistance.
The ionic liquid was modified onto graphene sheets using ultrasonic techniques.
The study examined how ionic liquid‐modified graphene affects LLDPE structure.
The thermal conductivity and mechanical properties of LLDPE were enhanced.
Associations between lyric and musical depth in Chinese songs: Evidence from computational modeling
Authors: Xu Liang , Xu Bingfei , Sun Zaoyi , Li Hongting 
Published: June 2024

AbstractMusical depth, which encompasses the intellectual and emotional complexity of music, is a robust dimension that influences music preference. However, there remains a dearth of research exploring the relationship between lyrics and musical depth. This study addressed this gap by analyzing linguistic inquiry and word count‐based lyric features extracted from a comprehensive dataset of 2372 Chinese songs. Correlation analysis and machine learning techniques revealed compelling connections between musical depth and various lyric features, such as the usage frequency of emotion words, time words, and insight words. To further investigate these relationships, prediction models for musical depth were constructed using a combination of audio and lyric features as inputs. The results demonstrated that the random forest regressions (RFR) that integrated both audio and lyric features yielded superior prediction performance compared to those relying solely on lyric inputs. Notably, when assessing the feature importance to interpret the RFR models, it became evident that audio features played a decisive role in predicting musical depth. This finding highlights the paramount significance of melody over lyrics in effectively conveying the intricacies of musical depth.
Crystallization kinetics analysis and modeling of aerospace PAEK materials
Authors: Ledesma Rodolfo , Wohl Christopher , Grimsley Brian 
Published: June 2024

AbstractPolyaryletherketone (PAEK) thermoplastic composite materials have received increasing attention for the manufacturing of composite structures. One manufacturing process of great interest for PAEK composite structures is automated fiber placement, which can increase the throughput of complex part fabrication and reduce the use of autoclaves for assembly of composite parts. Understanding the thermal effects of the material allows the control and adjustment of manufacturing variables to assure the integrity of the composite structure. PAEK resins and carbon fiber reinforced composites have been analyzed using differential scanning calorimetry to study crystallization kinetics. Isothermal and non‐isothermal tests were conducted, and the time‐dependent crystallization kinetics were modeled using the Velisaris and Seferis model for isothermal processes and the Gaussian process regression method for non‐isothermal processes. The results show the influence of the thermal conditions and the chemical structures considering the ketone content, and the effects of the presence of the carbon fibers on crystallization kinetics. The models utilized describe with high accuracy the time‐dependent crystallization kinetics of PAEK composite materials. An artificial neural network application was also implemented using the non‐isothermal PAEK composite models for further prediction of relative volume crystallinity and crystallization rate.Highlights
Polyaryletherketone (PAEK) materials crystallize differently depending on the crystallization conditions.
Carbon fibers influence the crystallization response in PAEK polymers.
Machine learning was used to characterize crystallization kinetics.
Activation energies were obtained for different thermal treatments.
Artificial neural network tool was developed for PAEK composites in non‐isothermal regimes.
Bullying begets bullying: A contagion model of bullying in Chinese adolescents
Authors: Limin Zhou , Chunguang Hu , Jie Huang 
Published: June 2024

AbstractPrevious studies have suggested that bullying may be contagious in adolescents. The present study examined whether ego depletion mediated the association between peer bullying and participant bullying and whether the mediating process was moderated by participant trait self‐control. A sample of 2217 Chinese high school students (16.92 ± 0.94 years; 1068 boys and 1084 girls) were invited to fill in the questionnaires. The results reveal that after controlling for gender, grade and neuroticism, ego depletion partially mediates the positive relationship between peer bullying and participant bullying. Further, participant trait self‐control moderates the relationship between peer bullying and participant bullying and that between peer bullying and participant ego depletion. That is, the strength of the contagion effect is lower in adolescents with high trait self‐control compared to those with low trait self‐control. In conclusion, this study provides empirical evidence of the contagion of bullying in adolescents. Limitations and implications for research and practice are discussed.
Dry‐air intrusion over India during break phases of the Indian summer monsoon in CMIP6 models
Authors: Singh Rahul , Sandeep S. 
Published: June 2024

AbstractEpisodes of dry‐air intrusion over northern India have been observed during break phases of the Indian summer monsoon (ISM). Previous investigations have provided observational evidence of a significant reservoir of unsaturated air over the northern Arabian Sea, serving as the source of this dry‐air intrusion. It was also suggested that the monsoon low‐level jet, which typically transports moisture to continental India during the active phase, instead transports dry air during the break phase of the ISM. While the existence of dry‐air intrusion is well‐documented through observations, its representation in climate models remains uncertain. It is important to enhance our understanding of the process of dry‐air advection in climate models to assess their fidelity in simulating the climate over the region. In this study, we quantify the extent of dry‐air intrusion and examine its mechanisms in simulations from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Most CMIP6 models analysed in this study simulate the observed pattern of dry‐air advection over continental India realistically during the summer monsoon‐break phase. Some models also simulate dry‐air transport from West Asia, possibly due to an overly smoothed representation of orography. Furthermore, the majority of CMIP6 models successfully capture the intrinsic modes associated with the dry monsoon phase, as demonstrated by empirical orthogonal function analysis of low‐level zonal winds. Our analyses indicate that global climate models exhibit better skill in simulating dry processes of the monsoon compared with moist processes. These findings uncover previously underexplored aspects of the monsoon, which are essential for assessing future regional climate changes accurately.
Designing of π‐Bridge for Metal Free Dye‐Sensitized Solar Cell and Optoelectronic Properties: An ab initio DFT Perspective
Authors: Kumar Rajneesh , Singh Ajeet 
Published: June 2024

AbstractWe have designed a series of donor‐π‐acceptor (D‐π‐A) based metal‐free organic dyes to improve the power conversion efficiency of dye‐sensitized solar cells (DSSCs) and optoelectronic properties. Density functional theory (DFT) and time‐dependent density functional theory (TD‐DFT) simulations have been performed to calculate the electronic and optical properties. The reduction of band gap is observed from 2.33 eV to 1.60 eV when we have strategically figure out the suitable π‐bridge. The band gaps 1.53 eV were observed with strong donor group. The ground and excited state oxidation potential, normal dipole moment, light harvesting efficiency, maximum absorption wavelength and electron injection properties were calculated for the designed dyes. Upon the screening of the π‐bridge, we have substituted the reference triphenylamine (TPA) donor group with other best‐known donor. The cyanoacrylic acid group was chosen as the acceptor group for designed dye molecules.The simulated absorption spectra show a bathochromic shift from 435 nm to 817 nm that infers the effect of such variation of the π‐bridging group. The rational designing of high‐performance organic‐based dye sensitizer molecule embark on the scientific community towards the advancement of renewable energy technologies
Modern ransomware: Evolution, methodology, attack model, prevention and mitigation using multi‐tiered approach
Authors: Raj Arpit , Narayan Vedant , Muskan Vivek , Sani Abhilash , Sharma Pankaj , Sarma S. S. 
Published: June 2024

AbstractRansomware is a menace to the vibrant digital ecosystem. The exponential growth in ransomware attacks, its detrimental impacts, and the ever‐changing methods adopted by threat actor groups demands a focused understanding of the evolution of ransomware. This would help the organizations devise novel defensive frameworks and security controls against the modern ransomware. In this work, the impacts and evolution of ransomware through different phases up to its current form are detailed. Further, based on the study and analysis of the most prevalent modern ransomware variants, their most used tactics, techniques and procedures (TTPs) are identified as per the MITRE ATT&CK model. This acts as a platform to propose a generic attack model for “modern ransomware.” Building on the existing MITRE mitigation, D3FEND‐based approaches and considering the resource and budget constraints of organizations, a simplified three‐tier defensive model that is cost‐effective and implementable is put forward. Thus, this work aims to open avenues for understanding the TTPs, and attack methodology of “modern ransomware,” thereby developing feasible and implementable defensive security controls.
Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories
Authors: Weller Julian , Migenda Nico , Liu Rui , Wegel Arthur , von Enzberg Sebastian , Kohlhase Martin , Schenck Wolfram , Dumitrescu Roman 
Published: June 2024

AbstractManufacturing systems are dynamic and exhibit increasing complexity and uncertainty. Smart manufacturing uses Data Analytics methods to optimize manufacturing processes, systems and products. One approach to structure use cases in production management in smart manufacturing is the Product-Process-Resource (PPR) model, where the resource executes a process on a given product. The PPR model needs to be extended for smart manufacturing, to meet the requirements of prescriptive analytics (but not exclusively). Our contributions are an extended PPR model for prescriptive analytics (P2PR) that involves environmental effects, expert knowledge and adds a process sub-model distinguishing between manufacturing and supervisory processes. We develop prescriptive analytics decision-making categories based on the area of validity and the degree of interconnectivity. The combination results in a systematization scheme for prescriptive analytics use cases in a smart factory environment. It assists entities to find shared characteristics in different prescriptive smart factory use cases within one production ecosystem. A mapping of prescriptive algorithms (as part of a use case) to a category and domain is enabled for future case studies.
Impact of scalar NSI on the neutrino mass ordering sensitivity at DUNE, HK and KNO
Authors: Sarker Arnab , Medhi Abinash , Bezboruah Dharitree , Devi Moon Moon , Dutta Debajyoti 
Published: June 2024

Abstract
The study of neutrino non-standard interactions (NSI) is a well-motivated phenomenological scenario to explore new physics beyond the Standard Model. The possible scalar coupling of neutrinos (ν) with matter is one of such new physics scenarios that appears as a sub-dominant effect that can impact the ν-oscillations in matter. The presence of scalar NSI introduces an additional contribution directly to the ν-mass matrix in the interaction Hamiltonian and subsequently to the ν-oscillations. This indicates that scalar NSI may have a significant impact on measurements related to ν-oscillations e.g. leptonic CP phase (δCP), θ23 octant and neutrino mass ordering (MO). The linear scaling of the effects of scalar NSI with matter density also motivates its exploration in long-baseline (LBL) experiments. In this paper, we study the impact of a scalar-mediated NSI on the MO sensitivity of DUNE, HK and HK+KNO, which are upcoming LBL experiments. We study the impact on MO sensitivities at these experiments assuming that scalar NSI parameters are present in nature and is known from other non-LBL experiments. We observe that the presence of diagonal scalar NSI elements can significantly affect the ν-mass ordering sensitivities. We then also combine the data from DUNE with HK and HK+KNO to explore possible synergy among these experiments in a wider parameter space. We also observe a significant enhancement in the MO sensitivities for the combined analysis.
Four top final states with NLO accuracy in perturbative QCD: 4 lepton channel
Authors: Dimitrakopoulos Nikolaos , Worek Malgorzata 
Published: June 2024

Abstract
Triggered by the observation of four top-quark production at the LHC by the ATLAS and CMS collaboration we report on the calculation of the next-to-leading order QCD corrections to the Standard Model process pp → $$ t\overline{t}t\overline{t} $$
t

t
¯

t

t
¯

in the 4ℓ top-quark decay channel. We take into account higher-order QCD effects in both the production and decays of the four top quarks. The latter effects are treated in the narrow width approximation, which preserves top-quark spin correlations throughout the calculation. We present results for two selected renormalisation and factorisation scale settings and three different PDF sets. Furthermore, we study the main theoretical uncertainties that are associated with the neglected higher-order terms in the perturbative expansion and with the parameterisation of the PDF sets. The results at the integrated and differential fiducial cross-section level are shown for the LHC Run III center-of-mass energy of $$ \sqrt{s} $$

s

= 13.6 TeV. Our findings are particularly relevant for precise measurements of the four top-quark fiducial cross sections and for the modelling of top-quark decays at the LHC.
Probing lepton number violation and Majorana nature of neutrinos at the LHC
Authors: Babu K. S. , Barman Rahool K. , Gonçalves Dorival , Ismail Ahmed 
Published: June 2024

Abstract
Observation of lepton number (L) violation by two units at colliders would provide evidence for the Majorana nature of neutrinos. We study signals of L-violation in the context of two popular models of neutrino masses, the type-II seesaw model and the Zee model, wherein small neutrino masses arise at the tree-level and one-loop level, respectively. We focus on L-violation signals at the LHC arising through the process pp → ℓ±ℓ′± + jets within these frameworks. We obtain sensitivity to L-violation in the type-II seesaw model for triplet scalar masses up to 700 GeV and in the Zee model for charged scalar masses up to 4.8 TeV at the high-luminosity LHC with an integrated luminosity of 3 ab−1.
Direct GPCR-EGFR interaction enables synergistic membrane-to-nucleus information transfer
Authors: Gekle Michael , Eckenstaler Robert , Braun Heike , Olgac Abdurrahman , Robaa Dina , Mildenberger Sigrid , Dubourg Virginie , Schreier Barbara , Sippl Wolfgang , Benndorf Ralf 
Published: June 2024

AbstractWe addressed the heteromerization of the epidermal growth factor receptor (EGFR) with G-protein coupled receptors (GPCR) on the basis of angiotensin-II-receptor-subtype-1(AT1R)-EGFR interaction as proof-of-concept and show its functional relevance during synergistic nuclear information transfer, beyond ligand-dependent EGFR transactivation. Following in silico modelling, we generated EGFR-interaction deficient AT1R-mutants and compared them to AT1R-wildtype. Receptor interaction was assessed by co-immunoprecipitation (CoIP), Förster resonance energy transfer (FRET) and fluorescence-lifetime imaging microscopy (FLIM). Changes in cell morphology, ERK1/2-phosphorylation (ppERK1/2), serum response factor (SRF)-activation and cFOS protein expression were determined by digital high content microscopy at the single cell level. FRET, FLIM and CoIP confirmed the physical interaction of AT1R-wildtype with EGFR that was strongly reduced for the AT1R-mutants. Responsiveness of cells transfected with AT1R-WT or –mutants to angiotensin II or EGF was similar regarding changes in cell circularity, ppERK1/2 (direct and by ligand-dependent EGFR-transactivation), cFOS-expression and SRF-activity. By contrast, the EGFR-AT1R-synergism regarding these parameters was completely absent for in the interaction-deficient AT1R mutants. The results show that AT1R-EGFR heteromerisation enables AT1R-EGFR-synergism on downstream gene expression regulation, modulating the intensity and the temporal pattern of nuclear AT1R/EGFR-information transfer. Furthermore, remote EGFR transactivation, via ligand release or cytosolic tyrosine kinases, is not sufficient for the complete synergistic control of gene expression.
Generation of realistic synthetic cable images to train deep learning segmentation models
Authors: MalvidoFresnillo Pablo , Mohammed Wael M. , Vasudevan Saigopal , PerezGarcia Jose A. , MartinezLastra Jose L. 
Published: June 2024

AbstractSemantic segmentation is one of the most important and studied problems in machine vision, which has been solved with high accuracy by many deep learning models. However, all these models present a significant drawback, they require large and diverse datasets to be trained. Gathering and annotating all these images manually would be extremely time-consuming, hence, numerous researchers have proposed approaches to facilitate or automate the process. Nevertheless, when the objects to be segmented are deformable, such as cables, the automation of this process becomes more challenging, as the dataset needs to represent their high diversity of shapes while keeping a high level of realism, and none of the existing solutions have been able to address it effectively. Therefore, this paper proposes a novel methodology to automatically generate highly realistic synthetic datasets of cables for training deep learning models in image segmentation tasks. This methodology utilizes Blender to create photo-realistic cable scenes and a Python pipeline to introduce random variations and natural deformations. To prove its performance, a dataset composed of 25000 synthetic cable images and their corresponding masks was generated and used to train six popular deep learning segmentation models. These models were then utilized to segment real cable images achieving outstanding results (over 70% IoU and 80% Dice coefficient for all the models). Both the methodology and the generated dataset are publicly available in the project’s repository.
Partnerschaftliche Gewalt gegen Männer
Authors: Landmann Aysche Maren , Feld Katharina , Schütte Clara , Yen Kathrin 
Published: June 2024

Zusammenfassung
Hintergrund
Die Problematik partnerschaftlicher Gewalt gegen Männer wird in der Forschung bisher nur zurückhaltend adressiert. Nur wenige aktuelle Untersuchungen zur Erfassung von Fallumständen und Befunden sowie dem Verhalten nach konkreten Gewalterfahrungen liegen vor.

Fragestellung
Ziel der vorliegenden Studie war es, Daten zu Erfahrungen von partnerschaftlicher Gewalt gegen Männer sowie zur Inanspruchnahme von Hilfe durch die Betroffenen zu erheben. Des Weiteren sollten Informationen zu Gewalterfahrungen in der Kindheit erfasst werden.

Material und Methoden
Zur Erhebung der Daten wurde ein Online-Fragebogen erstellt und an Beratungsorganisationen mit Bitte um Weiterleitung gesendet. Die Befragung fand zwischen Juli 2021 bis Juni 2022 statt. Die Daten wurden mit Excel und SPSS ausgewertet.

Ergebnisse
Insgesamt konnten Datensets von 163 Männern ausgewertet werden. Das durchschnittliche Alter der 163 Teilnehmer betrug 44,7 Jahre. Insgesamt 82,8 % der Teilnehmer erlebten bereits als Kind Gewalt, wobei sich signifikante Zusammenhänge zwischen dem Erleben von psychischer und körperlicher Gewalt (p < 0,001), aber auch zwischen dem Erleben von Gewalt durch die Eltern und in der Schule zeigten (p < 0,001). Die am häufigsten erlebte partnerschaftliche Gewalt war psychische Gewalt (90,2 %). 36,8 % der Teilnehmer sprachen mit niemandem über ihre Erlebnisse. Die am häufigsten genannten Gründe, keine Hilfe in Anspruch zu nehmen, waren das Bedürfnis, allein mit der Situation zurechtkommen zu wollen (50 %), und Unsicherheit über geeignete Ansprechpartner (46,7 %).

Diskussion
Medizinische Fachkräfte sollten für die Problematik verstärkt sensibilisiert werden. Auch sollten frühere oder aktuelle Gewalterfahrungen, z. B. im Rahmen von Check-up-Untersuchungen, abgefragt werden.