bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthetic reflection self-injection-locked microcombs
Authors: Ulanov Alexander E. , Wildi Thibault , Pavlov Nikolay G. , Jost John D. , Karpov Maxim , Herr Tobias 
Published: January 2024

AbstractLaser-driven microresonators have enabled chip-integrated light sources with unique properties, including the self-organized formation of ultrashort soliton pulses and frequency combs (microcombs). While poised to impact major photonic applications such as spectroscopy, sensing and optical data processing, microcombs still necessitate complex scientific equipment to achieve and maintain suitable single-pulse operation. Here to address this challenge, we demonstrate microresonators with programmable synthetic reflection providing tailored injection feedback to the driving laser. Synthetic reflection achieves independence from random sample scattering properties and, when designed appropriately, enables deterministic access to self-injection-locked microcombs operating exclusively in the single-soliton regime. These results provide a route to easily operable microcombs at scale for portable sensors, autonomous navigation or extreme-bandwidth data processing. The novel concept of synthetic reflection may also be generalized to other integrated photonic systems.
Disentanglement of single-cell data with biolord
Authors: Piran Zoe , Cohen Niv , Hoshen Yedid , Nitzan Mor 
Published: January 2024

AbstractBiolord is a deep generative method for disentangling single-cell multi-omic data to known and unknown attributes, including spatial, temporal and disease states, used to reveal the decoupled biological signatures over diverse single-cell modalities and biological systems. By virtually shifting cells across states, biolord generates experimentally inaccessible samples, outperforming state-of-the-art methods in predictions of cellular response to unseen drugs and genetic perturbations. Biolord is available at https://github.com/nitzanlab/biolord.
Vaccine design via antigen reorientation
Authors: Xu Duo , Carter Joshua J. , Li Chunfeng , Utz Ashley , Weidenbacher Payton A. B. , Tang Shaogeng , Sanyal Mrinmoy , Pulendran Bali , Barnes Christopher O. , Kim Peter S. 
Published: January 2024

AbstractA major challenge in creating universal influenza vaccines is to focus immune responses away from the immunodominant, variable head region of hemagglutinin (HA-head) and toward the evolutionarily conserved stem region (HA-stem). Here we introduce an approach to control antigen orientation via site-specific insertion of aspartate residues that facilitates antigen binding to alum. We demonstrate the generalizability of this approach with antigens from Ebola, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses and observe enhanced neutralizing antibody responses in all cases. We then reorient an H2 HA in an ‘upside-down’ configuration to increase the exposure and immunogenicity of HA-stem. The reoriented H2 HA (reoH2HA) on alum induced stem-directed antibodies that cross-react with both group 1 and group 2 influenza A subtypes. Electron microscopy polyclonal epitope mapping (EMPEM) revealed that reoH2HA (group 1) elicits cross-reactive antibodies targeting group 2 HA-stems. Our results highlight antigen reorientation as a generalizable approach for designing epitope-focused vaccines.
A ResNet-LSTM hybrid model for predicting epileptic seizures using a pretrained model with supervised contrastive learning
Authors: Lee Dohyun , Kim Byunghyun , Kim Taejoon , Joe Inwhee , Chong Jongwha , Min Kyeongyuk , Jung Kiyoung 
Published: January 2024

AbstractIn this paper, we propose a method for predicting epileptic seizures using a pre-trained model utilizing supervised contrastive learning and a hybrid model combining residual networks (ResNet) and long short-term memory (LSTM). The proposed training approach encompasses three key phases: pre-processing, pre-training as a pretext task, and training as a downstream task. In the pre-processing phase, the data is transformed into a spectrogram image using short time Fourier transform (STFT), which extracts both time and frequency information. This step compensates for the inherent complexity and irregularity of electroencephalography (EEG) data, which often hampers effective data analysis. During the pre-training phase, augmented data is generated from the original dataset using techniques such as band-stop filtering and temporal cutout. Subsequently, a ResNet model is pre-trained alongside a supervised contrastive loss model, learning the representation of the spectrogram image. In the training phase, a hybrid model is constructed by combining ResNet, initialized with weight values from the pre-trained model, and LSTM. This hybrid model extracts image features and time information to enhance prediction accuracy. The proposed method’s effectiveness is validated using datasets from CHB-MIT and Seoul National University Hospital (SNUH). The method’s generalization ability is confirmed through Leave-one-out cross-validation. From the experimental results measuring accuracy, sensitivity, and false positive rate (FPR), CHB-MIT was 91.90%, 89.64%, 0.058 and SNUH was 83.37%, 79.89%, and 0.131. The experimental results demonstrate that the proposed method outperforms the conventional methods.
Study on the influence law of cavities behind the shotcrete lining on the lattice girders
Authors: Qi Chuande , Liu Junfeng , Zong Chao , Jiang Weiliang , Li Weiteng , Li Yang , Yan Jianquan 
Published: January 2024

AbstractThe field monitoring data showed that a small amount of main reinforcement bars of lattice girder at the arch of a tunnel were pulled, and the calculation showed that the initial support structure should be compressed. To find out the reason for the tension of the main reinforcement, the geological radar was used to detect the cavity in the sprayed concrete layer at the tension position. In order to clarify the tension mechanism of the main reinforcement and the influence of factors such as the position and size of the cavity on the main reinforcement, numerical simulations were carried out. The results show that the cavity causes the eccentric compression of the shotcrete layer, resulting in moment of the lattice girder and the change of the stress distribution of the main reinforcement. The main reinforcement experiences tensile stress when the cavity size surpasses 3 m × 0.2 m, reaching a tensile stress of 81 MPa at a cavity size of 6 m × 0.2 m. Notably, the cavity located at the foot of the arch is more likely to produce substantial tensile stress on the primary reinforcement compared to those at the arch crown and waist. The research results provide a theoretical basis for the interpretation and analysis of tunnel lattice girder monitoring data.
Effect of atherosclerosis on the relationship between atrial fibrillation and ischemic stroke incidence among patients on hemodialysis
Authors: Joki Nobuhiko , Toida Tatsunori , Nakata Kenji , Abe Masanori , Hanafusa Norio , Kurita Noriaki 
Published: January 2024

AbstractIn patients undergoing hemodialysis, the impact of atrial fibrillation (AF) through cardiac thromboembolism on the development of ischemic stroke may be influenced by the severity of atherosclerosis present. However, there are no large-scale reports confirming whether the severity of atherosclerosis influences the relationship between AF and stroke development in patients requiring hemodialysis. We aimed to investigate the effects of atherosclerotic disease on the relationship between AF and new-onset ischemic stroke. This nationwide longitudinal study based on dialysis facilities across Japan used data collected from the Japanese Renal Data Registry at the end of 2019 and 2020. The exposure was AF at the end of 2019, identified using a resting 12-lead electrocardiography. The primary outcome was the incidence of cerebral infarction (CI) after 1 year. To examine whether the number of atherosclerotic diseases modified the association between AF and the outcome, we estimated the odds ratios (ORs) using a logistic regression model and then assessed the presence of global interaction using Wald test. Following the study criteria, data from 151,350 patients (mean age, 69 years; men, 65.2%; diabetic patients, 48.7%) were included in the final analysis. A total of 9841 patients had AF (prevalence, 6.5%). Between 2019 and 2020, 4967 patients (3.2%) developed ischemic stroke. The adjusted OR of AF for new-onset CI was 1.5, which showed a decreasing trend with an increasing number of atherosclerotic diseases; the interaction was not significant (P = 0.34). While age, diabetes mellitus, smoking, systolic blood pressure, and serum C-reactive protein concentration were positively associated with CI, intradialytic weight gain, body mass index, and serum albumin level were negatively associated. While we demonstrated the association between AF and new-onset CI among Japanese patients on hemodialysis, we failed to demonstrate the evidence that the association was attenuated with an increasing numbers of atherosclerotic complications.
A new design approach for dual-band power amplifiers based on dual-band HCC and bandpass filter
Authors: Zarghami Sepehr , Hayati Mohsen 
Published: January 2024

AbstractThis paper introduces a novel design approach based on the dual-band harmonic control circuit and bandpass filter for dual-band power amplifiers. The circuit schematic of the proposed approach is constructed using four resonators and RFC inductors. The first two resonators are dedicated to controlling the second harmonics, while the third and fourth resonators serve as a harmonic blocker, allowing only the main signals to pass through to the load. Subsequently, all components are replaced by circuits based on microstrip elements, forming the proposed OMN. This OMN includes a novel wideband bias circuit, elliptically coupled resonators, and a new dual-band bandpass filter. To ensure compatibility with the transistor, a compensator line has been integrated. As a result, a dual-band power amplifier has been fabricated and measured at two operating frequencies, 2.1 GHz and 2.91 GHz. The measured values for drain efficiency, output power, and power gain at 2.1 GHz are 75.98%, 37.5 dBm, and 12.5 dB, respectively. Similarly, at 2.91 GHz, these values are 75.73%, 37.24 dBm, and 12.24 dB, respectively.
Assessing antibody and nanobody nativeness for hit selection and humanization with AbNatiV
Authors: Ramon Aubin , Ali Montader , Atkinson Misha , Saturnino Alessio , Didi Kieran , Visentin Cristina , Ricagno Stefano , Xu Xing , Greenig Matthew , Sormanni Pietro 
Published: January 2024

AbstractMonoclonal antibodies have emerged as key therapeutics. In particular, nanobodies, small, single-domain antibodies that are naturally expressed in camelids, are rapidly gaining momentum following the approval of the first nanobody drug in 2019. Nonetheless, the development of these biologics as therapeutics remains a challenge. Despite the availability of established in vitro directed-evolution technologies that are relatively fast and cheap to deploy, the gold standard for generating therapeutic antibodies remains discovery from animal immunization or patients. Immune-system-derived antibodies tend to have favourable properties in vivo, including long half-life, low reactivity with self-antigens and low toxicity. Here we present AbNatiV, a deep learning tool for assessing the nativeness of antibodies and nanobodies, that is, their likelihood of belonging to the distribution of immune-system-derived human antibodies or camelid nanobodies. AbNatiV is a multipurpose tool that accurately predicts the nativeness of Fv sequences from any source, including synthetic libraries and computational design. It provides an interpretable score that predicts the likelihood of immunogenicity, and a residue-level profile that can guide the engineering of antibodies and nanobodies indistinguishable from immune-system-derived ones. We further introduce an automated humanization pipeline, which we applied to two nanobodies. Laboratory experiments show that AbNatiV-humanized nanobodies retain binding and stability at par or better than their wild type, unlike nanobodies that are humanized using conventional structural and residue-frequency analysis. We make AbNatiV available as downloadable software and as a webserver.
In situ architecture of Opa1-dependent mitochondrial cristae remodeling
Authors: Fry Michelle Y , Navarro Paula P , Hakim Pusparanee , Ananda Virly Y , Qin Xingping , Landoni Juan C , Rath Sneha , Inde Zintis , Lugo Camila Makhlouta , Luce Bridget E , Ge Yifan , McDonald Julie L , Ali Ilzat , Ha Leillani L , Kleinstiver Benjamin P , Chan David C , Sarosiek Kristopher A , Chao Luke H 
Published: January 2024

AbstractCristae membrane state plays a central role in regulating mitochondrial function and cellular metabolism. The protein Optic atrophy 1 (Opa1) is an important crista remodeler that exists as two forms in the mitochondrion, a membrane-anchored long form (l-Opa1) and a processed short form (s-Opa1). The mechanisms for how Opa1 influences cristae shape have remained unclear due to lack of native three-dimensional views of cristae. We perform in situ cryo-electron tomography of cryo-focused ion beam milled mouse embryonic fibroblasts with defined Opa1 states to understand how each form of Opa1 influences cristae architecture. In our tomograms, we observe a variety of cristae shapes with distinct trends dependent on s-Opa1:l-Opa1 balance. Increased l-Opa1 levels promote cristae stacking and elongated mitochondria, while increased s-Opa1 levels correlated with irregular cristae packing and round mitochondria shape. Functional assays indicate a role for l-Opa1 in wild-type apoptotic and calcium handling responses, and show a compromised respiratory function under Opa1 imbalance. In summary, we provide three-dimensional visualization of cristae architecture to reveal relationships between mitochondrial ultrastructure and cellular function dependent on Opa1-mediated membrane remodeling.
Nachbehandlung nach Knorpeltherapie am Kniegelenk – eine Empfehlung der AG Klinische Geweberegeneration der DGOU
Authors: Niethammer Thomas R. , Aurich Matthias , Brucker Peter U. , Faber Svea , Diemer Frank , Pietschmann Matthias F. , Schoch Wolfgang , Zinser Wolfgang , Müller Peter E. 
Published: January 2024

ZusammenfassungDie erste Nachbehandlungsempfehlung der AG Klinische Geweberegeneration der DGOU stammt aus dem Jahr 2012. Neue wissenschaftliche Evidenz und veränderte Rahmenbedingungen machten eine
Aktualisierung der Nachbehandlungsempfehlungen nach Knorpeltherapie erforderlich.Im Rahmen einer mehrstufigen Mitgliederbefragung wurde ein Konsensus erzielt, der gemeinsam mit der wissenschaftlichen Evidenz die Basis für die vorliegende Nachbehandlungsempfehlung
gibt.Das maßgebliche Kriterium für die Nachbehandlung ist weiterhin die Defektlokalisation. Dabei wird zwischen femorotibialen und patellofemoralen Defekten unterschieden. Zudem werden nun auch
weiterführende Kriterien bez. der Knorpeldefekte berücksichtigt (stabiler Knorpelrand, Lage außerhalb der Hauptbelastungszone) und auf die unterschiedlichen Verfahren der Knorpeltherapie (z. B.
osteochondrale Transplantation, Minced Cartilage) eingegangen.Die vorliegende aktualisierte Nachbehandlungsempfehlung beinhaltet unterschiedliche Aspekte der Nachbehandlung, beginnend vom frühen perioperativen Management bis zur Sportfreigabe und
Wiederaufnahme von Kontaktsport nach erfolgter Knorpeltherapie.
COVID-19 in Children with Chronic Kidney Disease; Does it Differ
Much?
Authors: Baltu Demet , Kurt-Sukur Eda Didem , Tastemel Ozturk Tugba , Gulhan Bora , Ozaltin Fatih , Duzova Ali , Topaloglu Rezan 
Published: January 2024

Abstract
Background COVID-19 is known to have a mild course in children, however
more data on pediatric chronic kidney disease (CKD) is needed. We aimed to
assess the incidence and severity of COVID-19 in pediatric CKD patients.
Methods A questionnaire including demographics, COVID-19 history,
symptoms, and vaccination status was applied to patients with CKD. We also
retrospectively reviewed the presentation and outcomes of SARS-CoV-2 infection
in this patient group from March 2020 to December 2021.
Results 220 patients were included, 48 were found to have experienced
COVID-19. There was no significant difference regarding age, gender, underlying
kidney disease, CKD stage, dialysis status, type or number of immunosuppressive
medications, and glomerular filtration rate between patients with and without
COVID-19. Most were infected by a household member (43.8%) and during
outpatient or inpatient care (18.8%). Four (8.3%) were
asymptomatic, and 43 (89.6%) had mild infection. Severe COVID-19 was
observed in only one patient. Eleven (22.9%) patients with COVID-19 were
previously vaccinated. Acute kidney injury was detected in 4 (8.3%); as
stage 1 in all. Median follow-up after COVID-19 was 4.6 months. All patients
fully recovered, and no renal disease flare or death was observed.
Conclusions Although the vaccination rate was low in our cohort, the
majority of the children with COVID-19 showed a mild course. Along with the
vaccination, general precautions seemed to be successful for this
population.
Computational Fluid Dynamics and Its Potential Applications for the ENT Clinician
Authors: Root Zachary T. , Schneller Aspen R. , Lepley Thomas J. , Wu Zhenxing , Zhao Kai 
Published: January 2024

AbstractThis article is an examination of computational fluid dynamics in the field of otolaryngology, specifically rhinology. The historical development and subsequent application of computational fluid dynamics continues to enhance our understanding of various sinonasal conditions and surgical planning in the field today. This article aims to provide a description of computational fluid dynamics, the methods for its application, and the clinical relevance of its results. Consideration of recent research and data in computational fluid dynamics demonstrates its use in nonhistological disease pathology exploration, accompanied by a large potential for surgical guidance applications. Additionally, this article defines in lay terms the variables analyzed in the computational fluid dynamic process, including velocity, wall shear stress, area, resistance, and heat flux.
Choice of language in the construction of cultural identity by Tamil speakers in India
Authors: Eldho Elizabeth , Kumar Rajesh 
Published: January 2024

Abstract
Individuals in multilingual societies are associated with several culturally diverse groups, and so their cultural
identity is multifarious and subject to constant change across time and space as a result of increasing intercultural engagements.
While cultural norms are essentially embedded in one’s language, the choice of language is understood as a significant tool in
projecting the cultural identity of a linguistic community. This paper examines how language choice becomes an agency for Tamil
speakers in India to construct their cultural identity. Contextualized among native Tamil speakers in Chennai, the capital city of
the southernmost Indian state of Tamil Nadu, this study unravels the narratives by which the speakers’ specific language
preference in family, friendship, and institutional domains is used to perform identities and maintain a community consciousness.
It also examines the role of language ideologies in contributing to their choices. The study finds that despite the penetration of
English into all three domains in varying degrees, Tamil remains the ‘pride’ and the preferred language for all. This affinity is
driven by ideological discourses surrounding the cultural history of Tamizhakam, from which arise the need to
form a distinct Tamil identity.
Spectroscopic analysis of hidden-charm pentaquarks
Authors: Sharma Ankush , Upadhyay Alka 
Published: January 2024

Abstract
In this work, the multiquark approach is used to analyze the spectroscopy of hidden-charm pentaquark states, motivated by recent discoveries at the LHCb collaboration. Using the SU(3) flavor representation, pentaquarks having J

P
= 5/2− are arranged into 10 (decuplet) of the SU(3) flavor multiplets. The masses of pentaquarks are calculated using the extension of the Gursey–Radicati mass formula and the effective mass scheme. Also, we calculated the magnetic moments of the hidden-charm pentaquarks using the effective mass and shielded charge technique. Further, we suggested the possible production modes for J

P
= 5/2− pentaquarks from the decay of bottom baryons, which consist of pentaquark states as intermediate states. Our results for masses demonstrate reasonable agreement with the available data and our analysis for both masses and magnetic moments may be useful for future experimental studies.
GMM-based GNSS spoofing detector using double differential phase measurement
Authors: Vinh La The , Nguyen Van Hien , Van Hiep Hoang , Dinh Thuan Nguyen , Hung Pham Ngoc , Ta Tung Hai 
Published: January 2024

Abstract
GNSS spoofing is an intentional interference wherein a GNSS receiver tracks counterfeit signals, resulting in incorrect outcome positions. This is the most dangerous type of intervention in the GNSS technology. In this study, we introduce a novel method for detecting spoofing signals using a Gaussian mixture model (GMM) on the double-carrier phase difference (DD) created by two independent receivers. The DD can completely eliminate errors caused by the satellite clock, receiver clock, and atmospheric layers; hence, the signal angle of arrival (AoA) is clearly expressed in the DD measurement. We utilized the GMM to model the probability density function of the DD measurement computed from the phase measurement of the receivers. Theoretically, AoA values of an authentic signal change over time owing to the nature of the signal broadcast from an orbiting satellite. However, fake signals are often transmitted from the generator, resulting in a central distribution of the corresponding AoA values. Existing studies deal with the spoofing detection problem using the above theoretical assumptions. However, it is practical to broadcast spoofing signals from several sources, and random noise can be mixed into the generated phase to render the DD measurement noisy. In such complicated scenarios, existing approaches are not sufficiently robust to detect non-authentic signals. Another observation is that because real satellites are moving in fixed orbits, there should be a correlation among the AoA values of the signals coming from these satellites. In contrast, counterfeit signals (with the main purpose of causing the wrong position or noisy phase) do not follow the pattern of the real signals. Therefore, instead of using the above hard assumption about the signal AoA, we propose a statistical model GMM to learn the hidden relationship of the AoA values among real signals from different real satellites, which are then used to detect spoofing signals.