bluuebunny/crossref_metadata_2025_split huggingface dataset:
Colorectal cancer risk stratification on histological slides based on survival curves predicted by deep learning
Authors: Höhn Julia , Krieghoff-Henning Eva , Wies Christoph , Kiehl Lennard , Hetz Martin J. , Bucher Tabea-Clara , Jonnagaddala Jitendra , Zatloukal Kurt , Müller Heimo , Plass Markus , Jungwirth Emilian , Gaiser Timo , Steeg Matthias , Holland-Letz Tim , Brenner Hermann , Hoffmeister Michael , Brinker Titus J. 
Published: September 2023

AbstractStudies have shown that colorectal cancer prognosis can be predicted by deep learning-based analysis of histological tissue sections of the primary tumor. So far, this has been achieved using a binary prediction. Survival curves might contain more detailed information and thus enable a more fine-grained risk prediction. Therefore, we established survival curve-based CRC survival predictors and benchmarked them against standard binary survival predictors, comparing their performance extensively on the clinical high and low risk subsets of one internal and three external cohorts. Survival curve-based risk prediction achieved a very similar risk stratification to binary risk prediction for this task. Exchanging other components of the pipeline, namely input tissue and feature extractor, had largely identical effects on model performance independently of the type of risk prediction. An ensemble of all survival curve-based models exhibited a more robust performance, as did a similar ensemble based on binary risk prediction. Patients could be further stratified within clinical risk groups. However, performance still varied across cohorts, indicating limited generalization of all investigated image analysis pipelines, whereas models using clinical data performed robustly on all cohorts.
Structural and functional insights into δ-poly-L-ornithine polymer biosynthesis from Acinetobacter baumannii
Authors: Patel Ketan D. , Gulick Andrew M. 
Published: September 2023

AbstractCationic homo-polyamino acid (CHPA) peptides containing isopeptide bonds of diamino acids have been identified from Actinomycetes strains. However, none has been reported from other bacteria. Here, we report a δ-poly-L-ornithine synthetase from Acinetobacter baumannii, which we name PosA. Surprisingly, structural analysis of the adenylation domain and biochemical assay shows L-ornithine as the substrate for PosA. The product from the enzymatic reaction was purified and identified as poly-L-ornithine composed of 7-12 amino acid units. Chemical labeling of the polymer confirmed the isopeptide linkage of δ-poly-L-ornithine. We examine the biological activity of chemically synthesized 12-mer δ-poly-L-ornithine, illustrating that the polymer may act as an anti-fungal agent. Structures of the isolated adenylation domain from PosA are presented with several diamino acids and biochemical assays identify important substrate binding residues. Structurally-guided genome-mining led to the identification of homologs with different substrate binding residues that could activate additional substrates. A homolog from Bdellovibrionales sp. shows modest activity with L-arginine but not with any diamino acids observed to be substrates for previously examined CHPA synthetases. Our study indicates the possibility that additional CHPAs may be produced by various microbes, supporting the further exploration of uncharacterized natural products.
Vector-chirality driven topological phase transitions in noncollinear antiferromagnets and its impact on anomalous Hall effect
Authors: Pradhan Subhadip , Samanta Kartik , Saha Kush , Nandy Ashis K. 
Published: September 2023

AbstractMagnetic materials showing topologically nontrivial quantum states with high tunability is an undoubtedly important topic in condensed matter physics and material science. Based on the first-principles electronic structure calculations and subsequent symmetry adapted effective low-energy k.p theory, we show in a noncollinear antiferromagnet (AFM), Mn3Sn, that the switching of the vector-chirality, κ, is an unconventional route to topological phase transition from a nodal-ring to a Weyl point semimetal. Specifically, we find that the switching of κ via staggered rotation leads to gapping out an elliptic nodal-ring everywhere at the Fermi-level except for a pair of points on the ring. As a consequence, the topological phase transition switches the anomalous Hall conductivity (AHC) from zero to a giant value. Furthermore, we theoretically demonstrate how the controlled manipulation of the chiral AFM order keeping κ unaltered favors unusual rotation of Weyl-points on the ring. In fact, without staggered rotation, this enables us to tune and switch the sign of in-plane components of the AHC by a collective uniform rotations of spins in the AFM unit cell.
Complex quantum network models from spin clusters
Authors: Chepuri Ravi T. C. , Kovács István A. 
Published: September 2023

AbstractIn the emerging quantum internet, complex network topology could lead to efficient quantum communication and robustness against failures. However, there are concerns about complexity in quantum communication networks, such as potentially limited end-to-end transmission capacity. These challenges call for model systems in which the impact of complex topology on quantum communication protocols can be explored. Here, we present a theoretical model for complex quantum communication networks on a lattice of spins, wherein entangled spin clusters in interacting quantum spin systems serve as communication links between appropriately selected regions of spins. Specifically, we show that ground state Greenberger-Horne-Zeilinger clusters of the two-dimensional random transverse-field Ising model can be used as communication links between regions of spins. Further, the resulting quantum networks can have complexity comparable to that of the classical internet. Our work provides a generative model for further studies towards determining the network characteristics of the emerging quantum internet.
The association between temperature and alcohol- and substance-related disorder hospital visits in New York State
Authors: Parks Robbie M. , Rowland Sebastian T. , Do Vivian , Boehme Amelia K. , Dominici Francesca , Hart Carl L. , Kioumourtzoglou Marianthi-Anna 
Published: September 2023

Abstract
Background
Limited evidence exists on how temperature increases are associated with hospital visits from alcohol- and substance-related disorders, despite plausible behavioral and physiological pathways.

Methods
In the present study, we implemented a case-crossover design, which controls for seasonal patterns, long-term trends, and non- or slowly-varying confounders, with distributed lag non-linear temperature terms (0–6 days) to estimate associations between daily ZIP Code-level temperature and alcohol- and substance-related disorder hospital visit rates in New York State during 1995–2014. We also examined four substance-related disorder sub-causes (cannabis, cocaine, opioid, sedatives).

Results
Here we show that, for alcohol-related disorders, a daily increase in temperature from the daily minimum (−30.1 °C (−22.2 °F)) to the 75th percentile (18.8 °C (65.8 °F)) across 0–6 lag days is associated with a cumulative 24.6% (95%CI,14.6%–34.6%) increase in hospital visit rates, largely driven by increases on the day of and day before hospital visit, with an association larger outside New York City. For substance-related disorders, we find evidence of a positive association at temperatures from the daily minimum (−30.1 °C (−22.2 °F)) to the 50th percentile (10.4 °C (50.7 °F)) (37.7% (95%CI,27.2%–48.2%), but not at higher temperatures. Findings are consistent across age group, sex, and social vulnerability.

Conclusions
Our work highlights how hospital visits from alcohol- and substance-related disorders are currently impacted by elevated temperatures and could be further affected by rising temperatures resulting from climate change. Enhanced social infrastructure and health system interventions could mitigate these impacts.
Broad sialic acid usage amongst species D human adenovirus
Authors: Mundy Rosie M. , Baker Alexander T. , Bates Emily A. , Cunliffe Tabitha G. , Teijeira-Crespo Alicia , Moses Elise , Rizkallah Pierre J. , Parker Alan L. 
Published: September 2023

AbstractHuman adenoviruses (HAdV) are widespread pathogens causing usually mild infections. The Species D (HAdV-D) cause gastrointestinal tract infections and epidemic keratoconjunctivitis (EKC). Despite being significant pathogens, knowledge around HAdV-D mechanism of cell infection is lacking. Sialic acid (SA) usage has been proposed as a cell infection mechanism for EKC causing HAdV-D. Here we highlight an important role for SA engagement by many HAdV-D. We provide apo state crystal structures of 7 previously undetermined HAdV-D fiber-knob proteins, and structures of HAdV-D25, D29, D30 and D53 fiber-knob proteins in complex with SA. Biologically, we demonstrate that removal of cell surface SA reduced infectivity of HAdV-C5 vectors pseudotyped with HAdV-D fiber-knob proteins, whilst engagement of the classical HAdV receptor CAR was variable. Our data indicates variable usage of SA and CAR across HAdV-D. Better defining these interactions will enable improved development of antivirals and engineering of the viruses into refined therapeutic vectors.
Reactivity variance between stereoisomers of saturated N-heterocyclic carbenes on gold surfaces
Authors: Kaur Gurkiran , Dominique Nathaniel L. , Hu Gaohe , Nalaoh Phattananawee , Thimes Rebekah L. , Strausser Shelby L. , Jensen Lasse , Camden Jon P. , Jenkins David M. 
Published: September 2023

Two stereoisomers, one C2 symmetric and one Cs symmetric, of saturated N-heterocyclic carbenes (NHCs) were placed on gold films and they demonstrate different reactivity.
Cost of Illness and Health-Related Quality of Life for Stuttering: Two Systematic Reviews
Authors: Norman Alicia , Lowe Robyn , Onslow Mark , O'Brian Sue , Packman Ann , Menzies Ross , Schroeder Liz 
Published: September 2023

Purpose:
For those who stutter, verbal communication is typically compromised in social situations. This may attract negative responses from listeners and stigmatization by society. These have the potential to impair health-related quality of life across a range of domains, including qualitative and quantitative impacts on speech output, mental health issues, and failure to attain educational and occupational potential. These systematic reviews were designed to explore this matter using traditional health economics perspectives of utility measures and cost of illness.

Method:
Studies were included if they involved children, adolescents, or adults with stuttering as a primary diagnosis. The quality of life search strategy identified 2,607 reports, of which three were included in the quality of life analysis. The cost of illness search strategy identified 3,778 reports, of which 39 were included in the cost of illness analysis.

Results:
Two of the three studies included in the quality of life analysis had a high risk of bias. When measured using utility scores, quality of life for people who stutter was in the range of those reported for chronic health conditions such as diabetes mellitus, cardiovascular disease, and cancer. However, there is little such evidence of quality of life impairment during the preschool years. Studies included in the cost of illness analysis carried considerable risk of bias overall.

Conclusions:
For people who stutter, there are substantive direct and indirect costs of illness. These include impairment, challenges, and distress across many domains throughout life, including income, education, employment, and social functioning. Evidence of quality of life impairment using utility measures is extremely limited. If this situation is not remedied, the lifetime impairment, challenges, and distress experienced by those who stutter cannot be documented in a form that can be used to influence health policy and health care spending.

Supplemental Material:

https://doi.org/10.23641/asha.24168201
Real‐time vehicle detection using segmentation‐based detection network and trajectory prediction
Authors: Zarei Nafiseh , Moallem Payman , Shams Mohammadreza 
Published: September 2023

AbstractThe position of vehicles is determined using an algorithm that includes two stages of detection and prediction. The more the number of frames in which the detection network is used, the more accurate the detector is, and the more the prediction network is used, the algorithm is faster. Therefore, the algorithm is very flexible to achieve the required accuracy and speed. YOLO's base detection network is designed to be robust against vehicle scale changes. Also, feature maps are produced in the detector network, which contribute greatly to increasing the accuracy of the detector. In these maps, using differential images and a u‐net‐based module, image segmentation has been done into two classes: vehicle and background. To increase the accuracy of the recursive predictive network, vehicle manoeuvres are classified. For this purpose, the spatial and temporal information of the vehicles are considered simultaneously. This classifier is much more effective than classifiers that consider spatial and temporal information separately. The Highway and UA‐DETRAC datasets demonstrate the performance of the proposed algorithm in urban traffic monitoring systems.
New convex approaches to general MVDR robust adaptive beamforming problems
Authors: Zhao Yao , Liu Qingsong , Tian He , Luo Mingfan , Ling Bingo Wing‐Kuen , Zhang Zhe 
Published: September 2023

AbstractConsider general minimum variance distortionless response (MVDR) robust adaptive beamforming problems based on the optimal estimation for both the desired signal steering vector and the interference‐plus‐noise covariance (INC) matrix. The optimal robust adaptive beamformer design problem is an array output power maximization problem, subject to three constraints on the steering vector, namely, a (convex or nonconvex) quadratic constraint ensuring that the direction‐of‐arrival (DOA) of the desired signal is separated from the DOA region of all linear combinations of the interference steering vectors, a double‐sided norm constraint, and a similarity constraint; as well as a ball constraint on the INC matrix, which is centered at a given data sample covariance matrix. To tackle the nonconvex problem, a new tightened semidefinite relaxation (SDR) approach is proposed to output a globally optimal solution; otherwise, a sequential convex approximation (SCA) method is established to return a locally optimal solution. The simulation results show that the MVDR robust adaptive beamformers based on the optimal estimation for the steering vector and the INC matrix have better performance (in terms of, e.g., the array output signal‐to‐interference‐plus‐noise ratio) than the existing MVDR robust adaptive beamformers by the steering vector estimation only.
Design of superconducting ultra‐wideband filter with wide stopband based on quintuple‐mode resonator
Authors: Kong Qingyu , Lu Xilong , Zhou Liguo , Zhang Rui , Zhou Shigang , Wei Bin , Jiang Linan 
Published: September 2023

AbstractIn this paper, a new ultra‐wideband (UWB) bandpass filter (BPF) based on QMR (quintuple‐mode resonator) loaded with quasi‐lumped elements is proposed for wide stopband application. The method of connecting five folded U‐shaped resonators with rectangular patches to construct a QMR was proposed. By adjusting the relative position of the rectangular patches, the frequency band width of the filter can be freely adjusted. Further, quasi‐lumped elements were loaded to the QMR to generate three transmission zeros to enhance stopband performance. The filter designed in this paper can independently adjust both the stopband and the passband, providing greater design flexibility. The passband of the final filter is 3.18–9.43 GHz, and the FBW (fractional relative bandwidth) is 99%. The out‐of‐band rejection is better than −15 dB in the frequency range of 9.6–28.42 GHz. The measurement results show good performance without any tuning, and are in good agreement with the simulation results.
Quantitative assessment on synchronisation capability of a line‐start permanent magnet synchronous motor with hybrid rotor
Authors: Yang Yubo , Yan Bo , Wang Xiuhe 
Published: September 2023

AbstractThe authors devote a quantitative assessment on the synchronisation capability of a line‐start permanent magnet synchronous motor (LSPMSM) equipped with a hybrid rotor. The quantitative assessment is realised by determining a load criterion consisting of load torques and inertias under which the motor will just synchronise. During the process of load‐criterion determination, close attention is paid to parameters governing the motor synchronisation behaviour. Following the principle of stator‐current error minimisation, the time‐variant magnetising inductances and permanent magnet (PM) flux linkages of the analysed LSPMSM are simplified into slip‐dependent constants via the simple and robust genetic algorithm (GA). The load criterion is then obtained after the establishment of a dynamic motor model involving the simplified parameters. Prototyping tests focused on motor speed‐time responses under different mechanical loads are carried out to validate the obtained load criterion and the paper analyses.
Design and implementation of a state estimator in a real distribution network
Authors: Vieyra Natanael , Angeles‐Camacho Cesar , Maya‐Ortiz Paul 
Published: September 2023

AbstractControlling and operating modern distribution networks are challenging tasks. The implementation of monitoring systems and the development of tools are helping to address this challenge. State estimators are one of the most promising tools for this purpose. These are used to reconstruct the current state of a system based on measurement outputs, which can then be used to design controllers that can adjust the inputs to achieve the desired output. This article deals with the problem of estimating the state of a real‐world distribution network. A combination of conventional supervisory control and data acquisition is used to estimate the state, together with a synchrophasor monitoring system. The proposed method uses the Fortescue transformation to separate the three‐phase coupled equations into three independent modal measurement equations. Single‐phase estimators based on the extended Kalman filter are used to solve three sub‐problems associated with the sequence reference frame, which correctly capture the transient and steady‐state behaviour of the distribution network. The proposed estimation method is easy to implement and robust to measure model noise and uncertainties. Furthermore, an already‐established distribution network tests the estimation scheme under various conditions.
Few‐shot electrical equipment image recognition method based on an improved two‐stage fine‐tuning approach
Authors: Wu Junpeng , Zeng Jiajun , Zhou Yibo , Zhang Ye , Zhang Yiwen 
Published: September 2023

AbstractIn the process of electrical equipment detection based on deep learning, insufficient image samples of the target equipment will lead to detection failure. To solve this problem, an object detection network and two‐stage fine‐tuning approach based on You Only Look Once (YOLO)v4 is proposed in this paper to achieve image recognition of electrical equipment under the condition of small samples. Using the two‐stage and dual‐network method as the training strategy, the data‐rich base class samples are used to train the sample classifier based on the modified cosine similarity in the base class training stage, and the fine‐tuning is carried out in the small sample new class training stage. In the training part, the improved Retinanet network is used for coarse detection and the YOLOv4 network with Convolutional Block Attention Module (CBAM) attentional mechanism module is inserted for fine detection. The experimental results show that the average accuracy of the proposed method under the settings of 5‐shot, 10‐shot, and 30‐shot is 31.6%, 34.3%, and 52.8%, respectively, which greatly improves the ability of electrical equipment identification under the condition of few‐shot.
The stability around Chariklo and the confinement of its rings
Authors: Giuliatti Winter S. M. , Madeira G. , Ribeiro T. , Winter O. C. , Barbosa G. O. , Borderes-Motta G. 
Published: September 2023

Context. Chariklo has two narrow and dense rings, C1R and C2R, located at 391 km and 405 km, respectively.
Aims. In the light of new stellar occultation data, we study the stability around Chariklo. We also analyse three confinement mechanisms that prevent the spreading of the rings, based on shepherd satellites in resonance with the edges of the rings.
Methods. This study was performed through a set of numerical simulations and the Poincaré surface of section technique.
Results. From the numerical simulation results, and from the current parameters referring to the shape of Chariklo, we verify that the inner edge of the stable region is much closer to Chariklo than the rings. The Poincaré surface of sections allows us to identify periodic and quasi-periodic orbits of the first kind, and also the resonant islands corresponding to the 1:2, 2:5, and 1:3 resonances. We construct a map of aeq versus eeq space that gives the location and width of the stable region and the 1:2, 2:5, and 1:3 resonances.
Conclusions. We find that the first kind periodic orbit family can be responsible for a stable region whose location and size meet that of C1R, for specific values of the ring particle eccentricities. However, C2R is located in an unstable region if the width of the ring is assumed to be about 120 m. After analysing different systems, we propose that the best confinement mechanism is composed of three satellites: two satellites shepherding the inner edge of C1R and the outer edge of C2R, and the third satellite trapped in the 1:3 resonance.
Liebe Leserinnen, liebe Leser …
Authors: Kluthe Bertil 
Published: September 2023

Paradigmenwechsel in der DiabetologieDie vergangenen zwei Jahrzehnte haben uns in zentralen Bereichen der Diabetestherapie
einen Paradigmenwechsel beschert, der uns den Weg zu einer anderen Sichtweise im
Bereich der Ernährungstherapie sowie neue Möglichkeiten bei den
technischen Hilfsmitteln und der medikamentösen Therapie eröffnet
hat.