bluuebunny/crossref_metadata_2025 huggingface dataset:
A highly sensitive AgNPs/Ni3(HHTP)2 SERS substrate for the detection of food additives and pesticide residues
Authors: Yuan YangTao , Zhou ZhengXian , Hao XuDong , Mi JiaJia , Cao Yu , Shi JianPing
Published: August 2024

Surface-enhanced Raman scattering (SERS) is a spectroscopic technique that utilizes nanostructured substrates and is vital in food analysis. However, enhancing SERS substrates’ sensitivity and applicability remains a challenge. The conductive metal organic framework Ni3(HHTP)2 has been widely used due to its excellent conductivity and porous structure. This study combines Ni3(HHTP)2’s charge transfer properties with AgNPs’s localized surface plasmon resonance to create a highly sensitive SERS substrate. Firstly, rod-shaped Ni3(HHTP)2 was prepared, and then a monolayer of AgNPs film was loaded on its surface. The substrate can detect crystal violet at a concentration of 10−14 M, and Ni3(HHTP)2 has a flat structure, coupled with AgNPs film, provided good detection uniformity (Relative Standard Deviation, RSD = 10.09%). Moreover, the substrate successfully detected food additives solutions, as well as the pesticide residues on fruit surfaces by bending. This substrate offers a rapid monitoring solution for food safety, facilitating real-time detection of contaminants in daily life.
Switchable multifunctional terahertz coding metasurface containing Dirac semimetal for wavefront manipulation
Authors: Zhang Yonggang , Wang Xuelin , Liu Yang , Wu Guifang , Wang Ziqun , Li Zhenhua , Yan Xin , Xu WeiYao , Yao Haiyun , Liang Lanju
Published: August 2024

Dirac semimetal (DSM) coding metasurfaces enable switchable beam control in the terahertz (THz) communication field, thereby providing additional options for the regulation of electromagnetic waves. This study proposes a new structure based on a DSM THz coding metasurface. By adjusting the DSM size, a coding metasurface containing eight units is constructed to realize 3-bit coding. Simultaneously, by adjusting the DSM Fermi level (E

F
), the relative phase delay of adjacent units is controlled, resulting in a switchable coding metasurface. Using specific coding arrangements, multi-functions, such as beam deflection, beam splitting, vortex beams, and vortex beams with adjustable deflection angles can be controlled. Furthermore, a reduce radar cross-section (by approximately 13 dB at an operating frequency of 1.05 THz), is achieved. This study provides novel concepts and methods for metamaterials in the fields of communication and radar.
Hidden Chaos in a new memristor-based discrete system with commensurate, incommensurate and variable fractional orders
Authors: Abbes Abderrahmane , Ouannas Adel , Hioual Amel , Momani Shaher
Published: August 2024

Memristors special qualities and potential to completely transform computing and memory technology have made them indispensable parts of many applications , which have attracted a lot of interest in complex dynamics. The manuscript focuses on an exhaustive exploration of the chaotic dynamical behaviors exhibited by memristor-based discrete systems under various fractional orders. Specifically, it scrutinizes three distinct variants: the memristor-based discrete system with commensurate fractional order, the memristor-based discrete system with incommensurate fractional order, and the memristor-based discrete system with variable fractional order. The study highlights how different fractional order cases can produce different dynamic patterns and chaotic behavior in the model. Each variant presents unique characteristics, such as the absence of a fixed point and the presence of multiple chaotic hidden attractors. To substantiate the theoretical assertions, a comprehensive array of numerical methods is employed, including bifurcation charts, phase portraits, and the computation of Lyapunov exponents. These techniques serve to validate the presence of chaotic attractors within the proposed variable fractional versions of the memristor-based discrete system. MATLAB R2024a simulations are conducted to further bolster the obtained findings, providing empirical validation and robustness to the theoretical conjectures put forth in the manuscript. Through this approach, the work offers valuable insights into the complex dynamics of memristor-based discrete systems under fractional orders, paving the way for future research and practical applications in the field of nonlinear dynamics and chaos theory.
Density-density correlation functions of chiral Luttinger liquids with a point-contact impurity
Authors: Danny Babu Nikhil , Setlur Girish S
Published: August 2024

The density-density correlation functions (most singular parts) of chiral Luttinger liquids forming the fractional quantum Hall effect (FQHE) edge are systematically derived in presence of a point-contact junction acting as a localised scalar impurity and are shown to be expressible as compact analytical functions with second order poles and involving the bare scale-independent reflection and transmission coefficients. The results are validated on comparison with standard fermionic perturbation theory. The linear response Hall conductance in the absence of a point-contact is recovered from the obtained density-density correlation functions (DDCF). The system under consideration is inhomogeneous with broken translational invariance and for such systems in one dimension, the connected moments of the density fluctuation operator beyond second order need not be included in order to retrieve the most singular parts of the correlations. The reason being that all odd moments of the density are zero and all higher order even moments are less singular than the quadratic moment. The implications of these results when used in conjunction with bosonization methods in presence of impurity backscattering is briefly discussed.
Relativistic and wide-angle corrections to galaxy power spectra
Authors: Jolicoeur Sheean , Guedezounme Sêcloka L. , Maartens Roy , Paul Pritha , Clarkson Chris , Camera Stefano
Published: August 2024

Galaxy surveys contain information on the largest scales via wide-angle and relativistic contributions. By combining two different galaxy populations, we can suppress the strong cosmic variance on ultra-large scales and thus enhance the detectability of the signals. The relativistic Doppler and Sachs-Wolfe effects are of a similar magnitude to the leading wide-angle corrections, so that it is important to treat them together, especially since they can partially cancel. The power spectra depend on the choice of line of sight for each galaxy pair and we present results for a general line of sight. Then we estimate the detection significance of the auto- and cross-power spectra for a variety of cases. We use two futuristic galaxy samples based on a `beyond-DESI' survey and a SKA Phase 2 survey, covering 15,000 deg2up toz=1. We find a detection significance for the total relativistic wide-angle effects that ranges from ~ 5σto >15σ, depending on the line-of-sight configuration.
Cosmic birefringence by dark photon
Authors: Lee Sung Mook , Kang Dong Woo , Gong Jinn-Ouk , Jeong Donghui , Jung Dong-Won , Park Seong Chan
Published: August 2024

We study the kinetic mixing between the cosmic microwave background (CMB) photon and the birefringent dark photon. These birefringent dark photon may exist in parity-violating dark sector, for example, through the coupling to axion field.
We show that the birefringence of the dark photon propagates to the CMB photon, but the resulting birefringence may not be isotropic over the sky, but will be anisotropic in general.
Moreover, our investigation sheds light on the essential role played by kinetic mixing in the generation of two fundamental characteristics of the CMB: circular polarization and spectral distortion.
Constraints on the energy spectrum of the diffuse cosmic neutrino flux from the ANTARES neutrino telescope
Authors: Albert A. , Alves S. , André M. , Ardid M. , Ardid S. , Aubert J.-J. , Aublin J. , Baret B. , Basa S. , Becherini Y. , Belhorma B. , Bendahman M. , Benfenati F. , Bertin V. , Biagi S. , Boumaaza J. , Bouta M. , Bouwhuis M.C. , Brânzaş H. , Bruijn R. , Brunner J. , Busto J. , Caiffi B. , Calvo D. , Campion S. , Capone A. , Carenini F. , Carr J. , Carretero V. , Cartraud T. , Celli S. , Cerisy L. , Chabab M. , Cherkaoui El Moursli R. , Chiarusi T. , Circella M. , Coelho J.A.B. , Coleiro A. , Coniglione R. , Coyle P. , Creusot A. , Díaz A.F. , De Martino B. , Distefano C. , Di Palma I. , Donzaud C. , Dornic D. , Drouhin D. , Eberl T. , Eddymaoui A. , van Eeden T. , van Eijk D. , El Hedri S. , El Khayati N. , Enzenhöfer A. , Fermani P. , Ferrara G. , Filippini F. , Fusco L.A. , Gagliardini S. , García J. , Gatius Oliver C. , Gay P. , Geißelbrecht N. , Glotin H. , Gozzini R. , Gracia Ruiz R. , Graf K. , Guidi C. , Haegel L. , van Haren H. , Heijboer A.J. , Hello Y. , Hennig L. , Hernández-Rey J.J. , Hößl J. , Huang F. , Illuminati G. , Jisse-Jung B. , de Jong M. , de Jong P. , Kadler M. , Kalekin O. , Katz U. , Kouchner A. , Kreykenbohm I. , Kulikovskiy V. , Lahmann R. , Lamoureux M. , Lazo A. , Lefèvre D. , Leonora E. , Levi G. , Le Stum S. , Loucatos S. , Manczak J. , Marcelin M. , Margiotta A. , Marinelli A. , Martínez-Mora J.A. , Migliozzi P. , Moussa A. , Muller R. , Navas S. , Nezri E. , Ó Fearraigh B. , Oukacha E. , Păun A. , Păvălaş G.E. , Peña-Martínez S. , Perrin-Terrin M. , Piattelli P. , Poirè C. , Popa V. , Pradier T. , Randazzo N. , Real D. , Riccobene G. , Romanov A. , Sánchez Losa A. , Saina A. , Salesa Greus F. , Samtleben D.F.E. , Sanguineti M. , Sapienza P. , Schüssler F. , Seneca J. , Spurio M. , Stolarczyk Th. , Taiuti M. , Tayalati Y. , Vallage B. , Vannoye G. , Van Elewyck V. , Viola S. , Vivolo D. , Wilms J. , Zavatarelli S. , Zegarelli A. , Zornoza J.D. , Zúñiga J. ,   The ANTARES collaboration
Published: August 2024

High-significance evidences of the existence of a high-energy diffuse flux of cosmic neutrinos have emerged in the last decade from several observations by the IceCube Collaboration. The ANTARES neutrino telescope took data for 15 years in the Mediterranean Sea, from 2007 to 2022, and collected a high-purity all-flavour neutrino sample. The search for a diffuse cosmic neutrino signal using this dataset is presented in this article. This final analysis did not provide a statistically significant observation of the cosmic diffuse flux. However, this is converted into limits on the properties of the cosmic neutrino spectrum. In particular, given the sensitivity of the ANTARES neutrino telescope between 1 and 50 TeV, constraints on single-power-law hypotheses are derived for the cosmic diffuse flux below 20 TeV, especially for power-law fits of the IceCube data with spectral index softer than 2.8.
Ultrasound pulse repetition frequency preferentially activates different neuron populations independent of cell type
Authors: Sherman Jack , Bortz Emma , Antonio Erynne San , Tseng Hua-an , Raiff Laura , Han Xue
Published: August 2024

Objective. Transcranial ultrasound (US) stimulation serves as an external input to a neuron, and thus the evoked response relies on neurons’ intrinsic properties. Neural activity is limited to a couple hundred hertz and often exhibits preference to input frequencies. Accordingly, US pulsed at specific physiologic pulse repetition frequencies (PRFs) may selectively engage neurons with the corresponding input frequency preference. However, most US parametric studies examine the effects of supraphysiologic PRFs. It remains unclear whether pulsing US at different physiologic PRFs could activate distinct neurons in the awake mammalian brain. Approach. We recorded cellular calcium responses of individual motor cortex neurons to US pulsed at PRFs of 10, 40, and 140 Hz in awake mice. We compared the evoked responses across these PRFs in the same neurons. To further understand the cell-type dependent effects, we categorized the recorded neurons as parvalbumin positive fast spiking interneurons or putative excitatory neurons and analyzed single-cell mechanosensitive channel expression in mice and humans using the Allen Brain Institute’s RNA-sequencing databases. Main results. We discovered that many neurons were preferentially activated by only one PRF and different PRFs selectively engaged distinct neuronal populations. US-evoked cellular calcium responses exhibited the same characteristics as those naturally occurring during spiking, suggesting that US increases intrinsic neuronal activity. Furthermore, evoked responses were similar between fast-spiking inhibitory neurons and putative excitatory neurons. Thus, variation in individual neuron’s cellular properties dominates US-evoked response heterogeneity, consistent with our observed cell-type independent expression patterns of mechanosensitive channels across individual neurons in mice and humans. Finally, US transiently increased network synchrony without producing prolonged over-synchronization that could be detrimental to neural circuit functions. Significance. These results highlight the feasibility of activating distinct neuronal subgroups by varying PRF and the potential to improve neuromodulation effects by combining physiologic PRFs.
Nonlinear model predictive control of a conductance-based neuron model via data-driven forecasting
Authors: Fehrman Christof , Daniel Meliza C
Published: August 2024

Objective. Precise control of neural systems is essential to experimental investigations of how the brain controls behavior and holds the potential for therapeutic manipulations to correct aberrant network states. Model predictive control, which employs a dynamical model of the system to find optimal control inputs, has promise for dealing with the nonlinear dynamics, high levels of exogenous noise, and limited information about unmeasured states and parameters that are common in a wide range of neural systems. However, the challenge still remains of selecting the right model, constraining its parameters, and synchronizing to the neural system. Approach. As a proof of principle, we used recent advances in data-driven forecasting to construct a nonlinear machine-learning model of a Hodgkin–Huxley type neuron when only the membrane voltage is observable and there are an unknown number of intrinsic currents. Main Results. We show that this approach is able to learn the dynamics of different neuron types and can be used with model predictive control (MPC) to force the neuron to engage in arbitrary, researcher-defined spiking behaviors. Significance. To the best of our knowledge, this is the first application of nonlinear MPC of a conductance-based model where there is only realistically limited information about unobservable states and parameters.
Development of a stereo-EEG based seizure matching system for clinical decision making in epilepsy surgery
Authors: Thomas John , Abdallah Chifaou , Jaber Kassem , Khweileh Mays , Aron Olivier , Doležalová Irena , Gnatkovsky Vadym , Mansilla Daniel , Nevalainen Päivi , Pana Raluca , Schuele Stephan , Singh Jaysingh , Suller-Marti Ana , Urban Alexandra , Hall Jeffery , Dubeau François , Maillard Louis , Kahane Philippe , Gotman Jean , Frauscher Birgit
Published: August 2024

Objective. The proportion of patients becoming seizure-free after epilepsy surgery has stagnated. Large multi-center stereo-electroencephalography (SEEG) datasets can allow comparing new patients to past similar cases and making clinical decisions with the knowledge of how cases were treated in the past. However, the complexity of these evaluations makes the manual search for similar patients impractical. We aim to develop an automated system that electrographically and anatomically matches seizures to those in a database. Additionally, since features that define seizure similarity are unknown, we evaluate the agreement and features among experts in classifying similarity. Approach. We utilized 320 SEEG seizures from 95 consecutive patients who underwent epilepsy surgery. Eight international experts evaluated seizure-pair similarity using a four-level similarity score. As our primary outcome, we developed and validated an automated seizure matching system by employing patient data marked by independent experts. Secondary outcomes included the inter-rater agreement (IRA) and features for classifying seizure similarity. Main results. The seizure matching system achieved a median area-under-the-curve of 0.76 (interquartile range, 0.1), indicating its feasibility. Six distinct seizure similarity features were identified and proved effective: onset region, onset pattern, propagation region, duration, extent of spread, and propagation speed. Among these features, the onset region showed the strongest correlation with expert scores (Spearman’s rho = 0.75, p< 0.001). Additionally, the moderate IRA confirmed the practicality of our approach with an agreement of 73.9% (7%), and Gwet’s kappa of 0.45 (0.16). Further, the interoperability of the system was validated on seizures from five centers. Significance. We demonstrated the feasibility and validity of a SEEG seizure matching system across patients, effectively mirroring the expertise of epileptologists. This novel system can identify patients with seizures similar to that of a patient being evaluated, thus optimizing the treatment plan by considering the results of treating similar patients in the past, potentially improving surgery outcome.
Kinetic profile inference with outlier detection using support vector machine regression and Gaussian process regression
Authors: Kim Minseok , Ko W.H. , Kwak Sehyun , Joung Semin , Lee Wonjun , Kim B. , Kim D. , Lee J.H. , Sung Choongki , Na Yong-Su , Ghim Y.-C.
Published: August 2024

We propose an outlier-resilient Gaussian process regression (GPR) model supported by support vector machine regression (SVMR) for kinetic profile inference. GPR, being a non-parametric regression using Bayesian statistics, has advantages in that it imposes no constraints on profile shapes and can be readily used to integrate different kinds of diagnostics, while it is vulnerable to the presence of even a single outlier among a measured dataset. As an outlier classifier, an optimized SVMR is developed based only on the measurements. Hyper-parameters of the developed GPR model with informative prior distributions are treated in two different ways, i.e. maximum a posteriori (MAP) estimator and marginalization using a Markov Chain Monte Carlo sampler. Our SVMR-supported GPR model is applied to infer ion temperature Ti
profiles using measured data from the KSTAR charge exchange spectroscopy system. The GPR-inferred Ti
profiles with and without an outlier are compared and show prominent improvement when the outlier is removed by the SVMR. Ti
profiles inferred with the MAP estimator and the marginalization scheme are compared. They are noticeably different when observation uncertainties are not small enough, and the marginalization scheme generally provides a smoother profile.
Experimental apparatus for condensed excited hydrogen research
Authors: Zeiner-Gundersen S.A. , Olafsson S.
Published: August 2024

In this article, we report on a versatile experimental instrument for the study of hydrogen, condensed excited hydrogen, and hydrogen Rydberg matter, charged particles, and radiation from these systems. The system allows researchers to attach different detectors to the chamber to study condensed hydrogen, Rydberg matter, or excited hydrogen under different conditions. We show how the system is used to excite hydrogen to Rydberg atoms while monitoring Rydberg states using lasers and time-of-flight (TOF) on ions with radiation monitoring. We verify some of the work on using clustered hydrogen and laser to accelerate particles from rest to relativistic velocity. The experimental setup is an advanced replication of the reactor and detection system setup reported by researchers from Goteborg University. This experimental instrument can be used to replicate more of the work performed by the research group at Gothenburg University on Rydberg Matter, charged-particle acceleration, and experiments on ultra-dense hydrogen (UDH).
Validated 3D finite-element model of the Risso’s dolphin (Grampus griseus) head anatomy demonstrates gular sound reception and channelling through the mandibular fats
Authors: Wei Chong , Erbe Christine , Smith Adam B , Yang Wei-Cheng
Published: August 2024

Like other odontocetes, Risso’s dolphins actively emit clicks and passively listen to the echoes during echolocation. However, the head anatomy of Risso’s dolphins differs from that of other odontocetes by a unique vertical cleft along the anterior surface of the forehead and a differently-shaped lower jaw. In this study, 3D finite-element sound reception and production models were constructed based on computed tomography (CT) data of a deceased Risso’s dolphin. Our results were verified by finding good agreement with experimental measurements of hearing sensitivity. Moreover, the acoustic pathway for sounds to travel from the seawater into the dolphin’s tympanoperiotic complexes (TPCs) was computed. The gular reception mechanism, previously discovered in Delphinus delphis and Ziphius cavirostris, was also found in this species. The received sound pressure levels and relative displacement at TPC surfaces were compared between the cases with and without the mandibular fats or mandible. The results demonstrate a pronounced wave-guiding role of the mandibular fats and a limited bone-conductor role of the mandible. For sound production modelling, we digitally filled the cleft with neighbouring soft tissues, creating a hypothetical ‘cleftless’ head. Comparison between sound travelling through a ‘cleftless’ head vs. an original head indicates that the distinctive cleft plays a limited role in biosonar sound propagation.
Symmetries for the 4HDM: II. Extensions by rephasing groups
Authors: Shao Jiazhen , Ivanov Igor P , Korhonen Mikko
Published: August 2024

We continue classification of finite groups which can be used as symmetry group of the scalar sector of the four-Higgs-doublet model (4HDM). Our objective is to systematically construct non-abelian groups via the group extension procedure, starting from the abelian groups A and their automorphism groups

Aut

(
A
)

. Previously, we considered all cyclic groups A available for the 4HDM scalar sector. Here, we further develop the method and apply it to extensions by the remaining rephasing groups A, namely

A
=

Z

2

×

Z

2

,

Z

4

×

Z

2

, and

Z

2

×

Z

2

×

Z

2

. As

Aut

(
A
)

grows, the procedure becomes more laborious, but we prove an isomorphism theorem which helps classify all the options. We also comment on what remains to be done to complete the classification of all finite non-abelian groups realizable in the 4HDM scalar sector without accidental continuous symmetries.
3-1-3 Weight averaging technique-based performance evaluation of deep neural networks for Alzheimer’s disease detection using structural MRI
Authors: Gautam Priyanka , Singh Manjeet
Published: August 2024

Alzheimer’s disease (AD) is a progressive neurological disorder. It is identified by the gradual shrinkage of the brain and the loss of brain cells. This leads to cognitive decline and impaired social functioning, making it a major contributor to dementia. While there are no treatments to reverse AD’s progression, spotting the disease’s onset can have a significant impact in the medical field. Deep learning (DL) has revolutionized medical image classification by automating feature engineering, removing the requirement for human experts in feature extraction. DL-based solutions are highly accurate but demand a lot of training data, which poses a common challenge. Transfer learning (TL) has gained attention for its knack for handling limited data and expediting model training. This study uses TL to classify AD using T1-weighted 3D Magnetic Resonance Imaging (MRI) from the Alzheimer’s Disease Neuroimaging (ADNI) database. Four modified pre-trained deep neural networks (DNN), VGG16, MobileNet, DenseNet121, and NASNetMobile, are trained and evaluated on the ADNI dataset. The 3-1-3 weight averaging technique and fine-tuning improve the performance of the classification models. The evaluated accuracies for AD classification are VGG16: 98.75%; MobileNet: 97.5%; DenseNet: 97.5%; and NASNetMobile: 96.25%. The receiver operating characteristic (ROC), precision–recall (PR), and Kolmogorov-Smirnov (KS) statistic plots validate the effectiveness of the modified pre-trained model. Modified VGG16 excels with area under the curve (AUC) values of 0.99 for ROC and 0.998 for PR curves. The proposed approach shows effective AD classification by achieving high accuracy using the 3-1-3 weight averaging technique and fine-tuning.
Introduction
Authors: Lewis Hannah
Published: August 2024

The introduction presents La La Land and its place in contemporary culture. It describes the debacle at the 2017 Oscars, when La La Land was mistakenly announced as the Best Picture winner, and suggests that the awkward mix-up was in many ways symbolic of the film’s broader cultural reception since its premiere. The film looked backward in some ways and forward in others, revealing much about the film musical genre’s enduring and evolving place in American culture. The introduction additionally presents the overall scope and argument of the book, briefly describes the plot and musical numbers, and outlines the major themes in the chapters that will follow.
Reception
Authors: Lewis Hannah
Published: August 2024

Chapter 5 examines La La Land’s reception, from its initial film festival run in the summer of 2016 through the Academy Awards ceremony in February 2017. Its evolving reception was shaped by several factors, including a shift in national mood in response to current events right around its premiere, as well as the simultaneous critical success of Moonlight, a film that symbolized a very different approach to diversity and representation. The reception of La La Land captured the essence of much broader cultural debates that were taking place around Hollywood, representation, and the kinds of stories and experiences that were being valued and presented onscreen.
Orff’s Narrative-Dramatic Cycle
Authors: Oade Stephanie
Published: August 2024

Chapter 8 considers Carl Orff’s Catulli Carmina from musical and dramatic perspectives. Although Orff’s cycle offered the suggestion of narrative, there were various challenges to overcome in order to create a sense of linear progression through the work. To this end Orff employed dramatic characters, speech, narrative voices, physical action, and stagecraft, in an attempt to move the lyric poems towards a dramatic presentation. The chapter also explores how Orff created a frame construct to objectify the poetry and impose Orffian symbolism on the original text. Although these dramatic adaptations create tension with the lyricism of the poems, the work offers an opportunity to explore the complex overlaps and incompatibilities between and within the genres of drama and lyric.
A Lyric Figure: Ariadne
Authors: Oade Stephanie
Published: August 2024

This chapter focuses on the figure of Ariadne who, in both Catullus 64 and Strauss–Hofmannsthal’s Ariadne auf Naxos, is constructed and presented as a lyric figure in her own right. This lyricism is considered from a variety of angles, including visual (in her isolation and liminality), stylistic (das Gleitende), thematic (shared concerns for marriage, sex, and death), and tonal (emotional subjectivity in her lament). Socio-cultural readings are introduced in order to interpret the two Ariadnes as models of femininity, mediated by their male creators and representative of their respective times. Her characterization raises discussion of her agency and transformative potential, concepts that are central to her interpretation in both works.
Strauss’s Musical Drama
Authors: Oade Stephanie
Published: August 2024

The final analysis chapter concentrates on the music of Richard Strauss. It offers a reading and interpretation of the music, contextualized by a wider discussion of Strauss’s musical style, including his orchestration, harmonic language, as well as his use of Wagnerian leitmotifs and historical pastiche. Strauss was perturbed by the essential lyricism of Hofmannsthal’s libretto and worked to counter this through the use of increasingly motivic language, thus creating the effect of musical narrative for a dramatic and progressive outline that leads to the ultimate transformation of both Ariadne and Bacchus. Study of Strauss’s musical fabric throws into relief many of Hofmannsthal’s lyric techniques and symbolic aims, whilst adding new dimensions to the interpretation of Catullus’s original poem.
Conclusion
Authors: Oade Stephanie
Published: August 2024

The volume closes by relating the conclusions of each case study to the wider conception of the lyric genre. It focuses on the limitations and advantages of seeking to establish a set of lyric characteristics, and the possibility of reading such lyric qualities across media during and through the process of reception. It also unravels the potential for lyric aspects to be embedded in narrative or dramatic forms, and questions the implications of this for the theorization of lyric and for the reading of Catullus. It establishes a framework for working with these ideas and sets the conclusions of the volume in a wider bibliographic context.
The Context: Ideas of Lyric
Authors: Oade Stephanie
Published: August 2024

This introduction to Part I outlines the context around the ideas of lyric that prevail in twenty-first-century scholarship. Since Part I seeks to establish a sense of the lyric tradition within which Catullus was working, this introduction begins with a discussion of some of the difficulties that surround the generic categorization of Catullus’s poetry and an overview of some of the influential ideas about Catullan lyricism from twentieth-century scholars. Two different approaches to generic categorization in lyric theory are laid out—the writer-led and the reader-led approaches—and these are used to establish methodological boundaries for the chapters that follow.
The Context: The Presence of Catullus 64 in Strauss–Hofmannsthal’s Ariadne auf Naxos
Authors: Oade Stephanie
Published: August 2024

Part IV: Lyric and Drama explores the opera Ariadne auf Naxos by Richard Strauss and Hugo von Hofmannsthal in conjunction with Catullus 64. The opera’s hitherto underestimated debt to Catullus sheds new light on its many generic and interpretative contradictions and helps to contextualize its experimental nature. Indeed, both Catullus 64 and Ariadne auf Naxos display generic hybridity, meaning that a joint study of the poem and opera offers the opportunity to explore the ways in which lyricism can be embedded within other genres, such as the narrative epyllion in hexameters and the dramatic opera form. The context section that opens Part IV outlines the relationship between the Strauss–Hofmannsthal opera and Catullus’s epyllion, poem 64. It focuses particularly on the ekphrasis and frame structures, as well as the parallel Ariadne figures, going on to contextualize the interpretation of Ariadne in the context of her wider reception in music. After an overview of both poem and opera, the respective educations of Strauss and Hofmannsthal are considered, as well as their ongoing engagement with the classics.
Harnessing large language models’ zero-shot and few-shot learning capabilities for regulatory research
Authors: Meshkin Hamed , Zirkle Joel , Arabidarrehdor Ghazal , Chaturbedi Anik , Chakravartula Shilpa , Mann John , Thrasher Bradlee , Li Zhihua
Published: August 2024

Large language models (LLMs) are sophisticated AI-driven models trained on vast sources of natural language data. They are adept at generating responses that closely mimic human conversational patterns. One of the most notable examples is OpenAI's ChatGPT, which has been extensively used across diverse sectors. Despite their flexibility, a significant challenge arises as most users must transmit their data to the servers of companies operating these models. Utilizing ChatGPT or similar models online may inadvertently expose sensitive information to the risk of data breaches. Therefore, implementing LLMs that are open source and smaller in scale within a secure local network becomes a crucial step for organizations where ensuring data privacy and protection has the highest priority, such as regulatory agencies. As a feasibility evaluation, we implemented a series of open-source LLMs within a regulatory agency’s local network and assessed their performance on specific tasks involving extracting relevant clinical pharmacology information from regulatory drug labels. Our research shows that some models work well in the context of few- or zero-shot learning, achieving performance comparable, or even better than, neural network models that needed thousands of training samples. One of the models was selected to address a real-world issue of finding intrinsic factors that affect drugs' clinical exposure without any training or fine-tuning. In a dataset of over 700 000 sentences, the model showed a 78.5% accuracy rate. Our work pointed to the possibility of implementing open-source LLMs within a secure local network and using these models to perform various natural language processing tasks when large numbers of training examples are unavailable.
HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction
Authors: Li Zhengwei , Wan Lipeng , Wang Lei , Wang Wenjing , Nie Ru
Published: August 2024

Numerous studies have demonstrated that microRNAs (miRNAs) are critically important for the prediction, diagnosis, and characterization of diseases. However, identifying miRNA–disease associations through traditional biological experiments is both costly and time-consuming. To further explore these associations, we proposed a model based on hybrid high-order moments combined with element-level attention mechanisms (HHOMR). This model innovatively fused hybrid higher-order statistical information along with structural and community information. Specifically, we first constructed a heterogeneous graph based on existing associations between miRNAs and diseases. HHOMR employs a structural fusion layer to capture structure-level embeddings and leverages a hybrid high-order moments encoder layer to enhance features. Element-level attention mechanisms are then used to adaptively integrate the features of these hybrid moments. Finally, a multi-layer perceptron is utilized to calculate the association scores between miRNAs and diseases. Through five-fold cross-validation on HMDD v2.0, we achieved a mean AUC of 93.28%. Compared with four state-of-the-art models, HHOMR exhibited superior performance. Additionally, case studies on three diseases—esophageal neoplasms, lymphoma, and prostate neoplasms—were conducted. Among the top 50 miRNAs with high disease association scores, 46, 47, and 45 associated with these diseases were confirmed by the dbDEMC and miR2Disease databases, respectively. Our results demonstrate that HHOMR not only outperforms existing models but also shows significant potential in predicting miRNA–disease associations.
HTINet2: herb–target prediction via knowledge graph embedding and residual-like graph neural network
Authors: Duan Pengbo , Yang Kuo , Su Xin , Fan Shuyue , Dong Xin , Zhang Fenghui , Li Xianan , Xing Xiaoyan , Zhu Qiang , Yu Jian , Zhou Xuezhong
Published: August 2024

Target identification is one of the crucial tasks in drug research and development, as it aids in uncovering the action mechanism of herbs/drugs and discovering new therapeutic targets. Although multiple algorithms of herb target prediction have been proposed, due to the incompleteness of clinical knowledge and the limitation of unsupervised models, accurate identification for herb targets still faces huge challenges of data and models. To address this, we proposed a deep learning-based target prediction framework termed HTINet2, which designed three key modules, namely, traditional Chinese medicine (TCM) and clinical knowledge graph embedding, residual graph representation learning, and supervised target prediction. In the first module, we constructed a large-scale knowledge graph that covers the TCM properties and clinical treatment knowledge of herbs, and designed a component of deep knowledge embedding to learn the deep knowledge embedding of herbs and targets. In the remaining two modules, we designed a residual-like graph convolution network to capture the deep interactions among herbs and targets, and a Bayesian personalized ranking loss to conduct supervised training and target prediction. Finally, we designed comprehensive experiments, of which comparison with baselines indicated the excellent performance of HTINet2 (HR@10 increased by 122.7% and NDCG@10 by 35.7%), ablation experiments illustrated the positive effect of our designed modules of HTINet2, and case study demonstrated the reliability of the predicted targets of Artemisia annua and Coptis chinensis based on the knowledge base, literature, and molecular docking.
PUNCH CD3-OLS: A Phase 3 Prospective Observational Cohort Study to Evaluate the Safety and Efficacy of Fecal Microbiota, Live-jslm (REBYOTA) in Adults With Recurrent Clostridioides difficile Infection
Authors: Feuerstadt Paul , Chopra Teena , Knapple Whitfield , Van Hise Nicholas W , Dubberke Erik R , Baggott Brian , Guthmueller Beth , Bancke Lindy , Gamborg Michael , Steiner Theodore S , Van Handel Daniel , Khanna Sahil
Published: August 2024

Background

The aim of this study was to evaluate the safety and efficacy of fecal microbiota, live-jslm (RBL; REBYOTA)—the first single-dose, broad consortia microbiota-based live biotherapeutic approved by the US Food and Drug Administration for preventing recurrent Clostridioides difficile infection (rCDI) in adults following standard-of-care (SOC) antibiotic treatment.

Methods

PUNCH CD3-OLS was a prospective, phase 3, open-label study, conducted across the US and Canada. Participants were aged ≥18 years with documented rCDI and confirmed use of SOC antibiotics. Participants with comorbidities including inflammatory bowel disease and mild-to-moderate immunocompromising conditions could be enrolled. A single dose of RBL was rectally administered within 24–72 hours of antibiotic completion. The primary endpoint was the number of participants with RBL- or administration-related treatment-emergent adverse events (TEAEs). Secondary endpoints included treatment success and sustained clinical response, at 8 weeks and 6 months after RBL administration, respectively.

Results

Overall, 793 participants were enrolled, of whom 697 received RBL. TEAEs through 8 weeks after administration were reported by 47.3% of participants; most events were mild or moderate gastrointestinal disorders. Serious TEAEs were reported by 3.9% of participants. The treatment success rate at 8 weeks was 73.8%; in participants who achieved treatment success, the sustained clinical response rate at 6 months was 91.0%. Safety and efficacy rates were similar across demographic and baseline characteristic subgroups.

Conclusions

RBL was safe and efficacious in participants with rCDI and common comorbidities. This is the largest microbiota-based live biotherapeutic study to date, and findings support use of RBL to prevent rCDI in a broad patient population.

Clinical Trials Registration

NCT03931941.
Non-dilated obstructive nephropathy
Authors: Feliciangeli Valeria , Noce Annalisa , Montalto Giulia , Germani Stefano , Miano Roberto , Asimakopoulos Anastasios D
Published: August 2024

Obstructive nephropathy (ON) is a common and reversible cause of post-renal acute kidney injury (AKI) and may be caused by a variety of conditions. It occurs when both the upper urinary tracts are obstructed, or when one tract is obstructed in patients with a solitary kidney. ON is suspected whenever there is evidence of hydronephrosis at imaging. However, not all patients with obstruction develop hydronephrosis and significant obstruction can be present in the absence of hydronephrosis. This syndrome is called non-dilated obstructive uropathy (NDOU). It accounts for about 5% of cases of urinary obstruction and the diagnosis can be challenging. The current paper provides an overview of the literature aiming to identify the main causes of NDOU and its clinical presentation, in order to clarify when to suspect it among AKI cases. A narrative review was performed due to the overall low quality of the available evidence. Only patients with post-renal AKI and a non-dilated or minimal dilation of the intrarenal collecting system were included. As evidenced by our review, NDOU is most prevalent in the fifth and sixth decades of life and affects mainly the male gender. On hospital admission serum creatinine levels are usually very high. Among the most common clinical presentations are oliguria/anuria, abdominal pain, signs of retention such as oedema or pleural effusion, and nausea/vomiting. About three out of four cases of NDOU are due to an ab-extrinsic compression of the ureters caused by retroperitoneal fibrosis or malignant disease. An effective and minimally invasive urinary diversion is obtained with ureteric stenting or a percutaneous nephrostomy. A correct diagnosis of NDOU may be challenging but it is of paramount importance as it can lead to a prompt management with a potential complete resolution of both obstruction and acute renal failure.
Cardiac adverse drug reactions to COVID-19 vaccines. A cross-sectional study based on the Europe-wide data
Authors: Nazar Wojciech , Romantowski Jan , Niedoszytko Marek , Daniłowicz-Szymanowicz Ludmiła
Published: August 2024

Aims

We aimed to analyse serious cardiac adverse drug reactions to COVID-19 vaccines from the Europe-wide EudraVigilance database.

Methods and results

In this retrospective, cross-sectional study, the EudraVigilance database was searched to identify suspected serious cardiac post-vaccination adverse drug reactions to COVID-19 vaccines. This data was coupled with the number of total vaccine doses administered in the European Economic Area for Comirnaty (Pfizer BioNTech), Spikevax (Moderna), Vaxzevria (AstraZeneca), Jcovden (Janssen), Nuvaxovid (Novavax), products, available from the European Centre for Disease Prevention and Control ‘Vaccine Tracker’ database. The analysis included 772 228 309 administered doses of eligible vaccines from the ‘Vaccine Tracker’ database and 86 051 eligible records of cardiac adverse drug reactions from the EudraVigilance database. The frequency of most of the investigated adverse drug reactions was very rare (<1/10 000 i.e. <100/1 000 000 doses). The lowest risk of any serious cardiac adverse drug reactions was noticed for vaccination with Comirnaty (135.5 per million doses), while Spikevax, Jcovden, Vaxzevria, and Nuvaxovid were characterized by higher risk (respectively, 140.9, 194.8, 313.6, and 1065.2 per million doses). The most common complications of vaccinations included syncope, arrhythmia, tachycardia, palpitations, angina pectoris, hypertension, myocarditis, thrombosis, and pulmonary embolism.

Conclusion

The risk of serious cardiac adverse drug reactions to COVID-19 vaccines is low and the benefit of active immunization against that disease seems to outweigh the potential risk of serious post-vaccination cardiac adverse drug reactions.
A case of large aneurysms of the coronary arteries and abdominal aorta in an infant
Authors: Sasikumar Deepa , Bhattacharya Deepanjan , Ayyappan Anoop , Shivanesan Pitchai
Published: August 2024

Aneurysms of the coronary arteries and abdominal aorta are extremely rare in infancy. Due to the rarity of the anomaly, there are no existing guidelines on management of these aneurysms. We describe the challenges in diagnosis, evaluation and management of an infantile Marfan with this rare presentation.
Impact of effective refractory period personalization on arrhythmia vulnerability in patient-specific atrial computer models
Authors: Martínez Díaz Patricia , Dasí Albert , Goetz Christian , Unger Laura A , Haas Annika , Luik Armin , Rodríguez Blanca , Dössel Olaf , Loewe Axel
Published: August 2024

Aims

The effective refractory period (ERP) is one of the main electrophysiological properties governing arrhythmia, yet ERP personalization is rarely performed when creating patient-specific computer models of the atria to inform clinical decision-making. This study evaluates the impact of integrating clinical ERP measurements into personalized in silico models on arrhythmia vulnerability.

Methods and results

Clinical ERP measurements were obtained in seven patients from multiple locations in the atria. Atrial geometries from the electroanatomical mapping system were used to generate personalized anatomical atrial models. The Courtemanche M. et al. cellular model was adjusted to reproduce patient-specific ERP. Four modeling approaches were compared: homogeneous (A), heterogeneous (B), regional (C), and continuous (D) ERP distributions. Non-personalized approaches (A and B) were based on literature data, while personalized approaches (C and D) were based on patient measurements. Modeling effects were assessed on arrhythmia vulnerability and tachycardia cycle length, with sensitivity analysis on ERP measurement uncertainty. Mean vulnerability was 3.4 ± 4.0%, 7.7 ± 3.4%, 9.0 ± 5.1%, and 7.0 ± 3.6% for scenarios A–D, respectively. Mean tachycardia cycle length was 167.1 ± 12.6 ms, 158.4 ± 27.5 ms, 265.2 ± 39.9 ms, and 285.9 ± 77.3 ms for scenarios A–D, respectively. Incorporating perturbations to the measured ERP in the range of 2, 5, 10, 20, and 50 ms changed the vulnerability of the model to 5.8 ± 2.7%, 6.1 ± 3.5%, 6.9 ± 3.7%, 5.2 ± 3.5%, and 9.7 ± 10.0%, respectively.

Conclusion

Increased ERP dispersion had a greater effect on re-entry dynamics than on vulnerability. Inducibility was higher in personalized scenarios compared with scenarios with uniformly reduced ERP; however, this effect was reversed when incorporating fibrosis informed by low-voltage areas. Effective refractory period measurement uncertainty up to 20 ms slightly influenced vulnerability. Electrophysiological personalization of atrial in silico models appears essential and requires confirmation in larger cohorts.
Model constraints on infiltration of surface-derived fluids deep into the brittle crust
Authors: Simpson Guy
Published: August 2024

Downward flow of surface-derived water deep into the upper crust is investigated using 2-D coupled hydrothermal numerical models. In the models, downward flow is driven by either topographic gradients or seismic pumping, while it is facilitated by large episodic variations in fault permeability, intended to mimic fracturing and healing on a fault over repeated seismic cycles. The models show that both forcing scenarios are equally capable of driving surface-derived fluid to the base of faults at 10 km depth in several tens of thousands of years under certain conditions. Downward flow of cold fluid occurs almost exclusively during and shortly after earthquakes, while during the remaining portion of the seismic cycle fluids remain relatively stationary while they undergo thermal relaxation (i.e. heating). Rapid downward flow is favoured by a large coseismic permeability, long permeability healing timescale and large coseismic dilatancy or high topographic relief above the fault at the surface. However, downward fluid flow is completely inhibited if fluid pressures exceeds the hydrostatic gradient, even by modest amounts, which suggests that deep fluid infiltration is unlikely to occur in every region.