bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel planning framework for efficient spot-scanning proton arc therapy via particle swarm optimization (SPArc-particle swarm)
Authors: Qian Yujia , Fan Qingkun , Dao Riao , Li Xiaoqiang , Yang Zhijian , Zhang Sheng , Yang Kunyu , Quan Hong , Tu Biao , Ding Xuanfeng , Liu Gang 
Published: December 2023

Abstract

Objective. Delivery efficiency is the bottleneck of spot-scanning proton arc therapy (SPArc) because of the numerous energy layers (ELs) ascending switches. This study aims to develop a new algorithm to mitigate the need for EL ascending via water equivalent thickness (WET) sector selection followed by particle swarm optimization (SPArc-particle swarm). Approach. SPArc-particle swarm divided the full arc trajectory into the optimal sectors based on K-means clustering analysis of the relative mean WET. Within the sector, particle swarm optimization was used to minimize the total energy switch time, optimizing the energy selection integrated with the EL delivery sequence and relationship. This novel planning framework was implemented on the open-source platform matRad (Department of Medical Physics in Radiation Oncology, German Cancer Research Center-DKFZ). Three representative cases (brain, liver, and prostate cancer) were selected for testing purposes. Two kinds of plans were generated: SPArc_seq and SPArc-particle swarm. The plan quality and delivery efficiency were evaluated. Main results. With a similar plan quality, the delivery efficiency was significantly improved using SPArc-particle swarm compared to SPArc_seq. More specifically, it reduces the number of ELs ascending switching compared to the SPArc_seq (from 21 to 7 in the brain, from 21 to 5 in the prostate, from 21 to 6 in the liver), leading to a 16%–26% reduction of the beam delivery time (BDT) in the SPArc treatment. Significance. A novel planning framework, SPArc-particle swarm, could significantly improve the delivery efficiency, which paves the roadmap towards routine clinical implementation.
Mechanocardiography detects improvement of systolic function caused by resynchronization pacing
Authors: Tokmak Fadime , Koivisto Tero , Lahdenoja Olli , Vasankari Tuija , Jaakkola Samuli , Airaksinen K E Juhani 
Published: December 2023

Abstract

Objective. Cardiac resynchronization therapy (CRT) is commonly used to manage heart failure with dyssynchronous ventricular contraction. CRT pacing resynchronizes the ventricular contraction, while AAI (single-chamber atrial) pacing does not affect the dyssynchronous function. This study compared waveform characteristics during CRT and AAI pacing at similar pacing rates using seismocardiogram (SCG) and gyrocardiogram (GCG), collectively known as mechanocardiogram (MCG). Approach. We included 10 patients with heart failure with reduced ejection fraction and previously implanted CRT pacemakers. ECG and MCG recordings were taken during AAI and CRT pacing at a heart rate of 80 bpm. Waveform characteristics, including energy, vertical range (amplitude) during systole and early diastole, electromechanical systole (QS2) and left ventricular ejection time (LVET), were derived by considering 6 MCG axes and 3 MCG vectors across frequency ranges of >1 Hz, 20–90 Hz, 6–90 Hz and 1–20 Hz. Main results. Significant differences were observed between CRT and AAI pacing. CRT pacing consistently exhibited higher energy and vertical range during systole compared to AAI pacing (p < 0.05). However, QS2, LVET and waveform characteristics around aortic valve closure did not differ between the pacing modes. Optimal differences were observed in SCG-Y, GCG-X, and GCG-Y axes within the frequency range of 6–90 Hz. Significance. The results demonstrate significant differences in MCG waveforms, reflecting improved mechanical cardiac function during CRT. This information has potential implications for predicting the clinical response to CRT. Further research is needed to explore the differences in signal characteristics between responders and non-responders to CRT.
Quantum walks-based simple authenticated quantum cryptography protocols for secure wireless sensor networks
Authors: Alanezi Ahmad , Abd El-Latif Ahmed A , Kolivand Hoshang , Abd-El-Atty Bassem 
Published: December 2023

Abstract
Wireless sensor networks (WSNs) play a crucial role in various applications, ranging from environmental monitoring to industrial automation that require high levels of security. With the development of quantum technologies, many security mechanisms may be hacked due to the promising capabilities of quantum computation. To address this challenge, quantum protocols have emerged as a promising solution for enhancing the security of wireless sensor communications. One of the common types of quantum protocols is quantum key distribution (QKD) protocols, which are investigated to allow two participants with fully quantum capabilities to share a random secret key, while semi-quantum key distribution (SQKD) protocols are designed to perform the same task using fewer quantum resources to make quantum communications more realizable and practical. Quantum walk (QW) plays an essential role in quantum computing, which is a universal quantum computational paradigm. In this work, we utilize the advantages of QW to design three authenticated quantum cryptographic protocols to establish secure channels for data transmission between sensor nodes: the first one is authenticated quantum key distribution (AQKD), the second one is authenticated semi-quantum key distribution (ASQKD) with one of the two participants having limited quantum capabilities, and the last one is ASQKD but both legitimate users possess limited quantum resources. The advantages of the proposed protocols are that the partners can exchange several different keys with the same exchanged qubits, and the presented protocols depend on a one-way quantum communication channel. In contrast, all previously designed SQKD protocols rely on two-way quantum communication. Security analyses prove that the presented protocols are secure against various well-known attacks and highly efficient. The utilization of the presented protocols in wireless sensor communications opens up new avenues for secure and trustworthy data transmission, enabling the deployment of resilient WSNs in critical applications. This work also paves the way for future exploration of quantum-based security protocols and their integration into WSNs for enhanced data protection.
Three-dimensional bound states of cylindrical quantum heterostructures with position-dependent mass carriers
Authors: Christiansen H R , Lima R M 
Published: December 2023

Abstract
We present a comprehensive spectral analysis of cylindrical quantum heterostructures by considering effective electronic carriers with position-dependent mass for five different kinetic-operator orderings. We obtain the bound energy eigenstates of particles in a three-dimensional cylindrical nanowire under a confining hyperbolic potential with both open and closed boundary conditions in the radial and the axial directions. In the present model we consider carriers with continuous mass distributions within the dot with abrupt mass discontinuities at the barriers, moving in a quantum dot that connects different substances. Continuity of mass and potential at the interfaces with the external layers result as a particular case. Our approach is mostly analytical and allows a precise comparison among von Roos ordering classes.
Thermal quantum coherence of two–qutrit Heisenberg XXZ model with Herring-Flicker coupling and Dzyaloshinskii-Moriya interaction under magnetic field
Authors: Adnane Brahim , Moqine Younes , Belouad Abdelhadi , El Bouâzzaoui Choubabi , Houça Rachid 
Published: December 2023

Abstract
In this study, we use the concept of l
1-norm coherence to characterize the entanglement of a two–qutrit Heisenberg XXZ model for subject to a uniform magnetic field and z–axis Dzyaloshinskii–Moriya interaction with Herring-Flicker coupling. We show that the temperature, magnetic field, DM interaction, and distance of Herring-Flicker coupling can all control the entanglement. However, the state system becomes less entangled at high temperatures or strong magnetic fields and vice versa. Our findings suggest that entanglement rises when the z–axis DM interaction increases. Additionally, we show that plateau behavior in the entanglement between spins (1, 1) occurs in the XXZ Heisenberg spin system and is influenced by the magnetic field, demonstrating that thermal agitation can weaken entanglement plateaus. Moreover, by setting the strengths coupling of the spin, we quickly recover the isotropic XY and XXX Heisenberg models. Finally, Herring-Flicker coupling affects the degree of entanglement. When Herring-Flicker coupling and temperature are at small values, the degree of entanglement is at its highest. Still, when Herring-Flicker coupling is at substantial values, the degree of entanglement tends to stabilize.
A scalable system to measure contrail formation on a per-flight basis
Authors: Geraedts Scott , Brand Erica , Dean Thomas R , Eastham Sebastian , Elkin Carl , Engberg Zebediah , Hager Ulrike , Langmore Ian , McCloskey Kevin , Yue-Hei Ng Joe , Platt John C , Sankar Tharun , Sarna Aaron , Shapiro Marc , Goyal Nita 
Published: December 2023

Abstract
Persistent contrails make up a large fraction of aviation's contribution to global warming. We describe a scalable, automated detection and matching (ADM) system to determine from satellite data whether a flight has made a persistent contrail. The ADM system compares flight segments to contrails detected by a computer vision algorithm running on images from the GOES-16 Advanced Baseline Imager. We develop a flight matching algorithm and use it to label each flight segment as a match or non-match. We perform this analysis on 1.6 million flight segments. The result is an analysis of which flights make persistent contrails several orders of magnitude larger than any previous work. We assess the agreement between our labels and available prediction models based on weather forecasts. Shifting air traffic to avoid regions of contrail formation has been proposed as a possible mitigation with the potential for very low cost/ton-CO2e. Our findings suggest that imperfections in these prediction models increase this cost/ton by about an order of magnitude. Contrail avoidance is a cost-effective climate change mitigation even with this factor taken into account, but our results quantify the need for more accurate contrail prediction methods and establish a benchmark for future development.
Initiative to reduce unnecessary routine daily testing of complete blood counts across 11 safety net hospitals
Authors: Cho Hyung J , Israilov Sigal , Tsega Surafel , Alaiev Dan , Talledo Joseph , Chandra Komal , Alarcon Manchego Peter , Zaurova Milana , Petrilli Christopher M , Krouss Mona 
Published: December 2023

Abstract

Objectives
National societies recommend against performing routine daily laboratory testing without a specific indication. Unnecessary testing can lead to patient harm, such as hospital-acquired anemia. The objective of this study was to reduce repeat complete blood counts (CBCs) after initial testing.

Methods
This was a quality improvement initiative implemented across 11 safety net hospitals in New York City. A best practice advisory (BPA) was implemented that asked the user to remove a CBC if the last 2 CBCs within 72 hours had normal white blood cell and platelet counts and unchanged hemoglobin levels. The outcome measure was the rate of CBCs per 1000 patient days preintervention (January 8, 2020, to December 22, 2020) to postintervention (December 23, 2020, to December 7, 2021). The process measure was the acceptance rate of the BPA, defined as the number of times the repeat CBC order was removed through the BPA divided by the total number of times the BPA triggered.

Results
Across 11 hospitals, repeat CBC testing decreased by 12.3% (73.05 to 64.04 per 1000 patient days, P &lt; .001). Six of the 11 hospitals exhibited statistically significant decreases, ranging from a 10% to 48.9% decrease of repeat CBCs. The overall BPA action rate was 20.0% (24,029 of 119,944 repeat CBCs).

Conclusions
This low-effort, electronic health record–based intervention can effectively reduce unnecessary laboratory testing.
Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering
Authors: Zheng Jiahao , Yang Yuedong , Dai Zhiming 
Published: December 2023

Abstract
Single-cell Hi-C (scHi-C) technology enables the investigation of 3D chromatin structure variability across individual cells. However, the analysis of scHi-C data is challenged by a large number of missing values. Here, we present a scHi-C data imputation model HiC-SGL, based on Subgraph extraction and graph representation learning. HiC-SGL can also learn informative low-dimensional embeddings of cells. We demonstrate that our method surpasses existing methods in terms of imputation accuracy and clustering performance by various metrics.
Integrating somatic mutation profiles with structural deep clustering network for metabolic stratification in pancreatic cancer: a comprehensive analysis of prognostic and genomic landscapes
Authors: Zou Min , Li Honghao , Su Dongqing , Xiong Yuqiang , Wei Haodong , Wang Shiyuan , Sun Hongmei , Wang Tao , Xi Qilemuge , Zuo Yongchun , Yang Lei 
Published: December 2023

Abstract
Pancreatic cancer is a globally recognized highly aggressive malignancy, posing a significant threat to human health and characterized by pronounced heterogeneity. In recent years, researchers have uncovered that the development and progression of cancer are often attributed to the accumulation of somatic mutations within cells. However, cancer somatic mutation data exhibit characteristics such as high dimensionality and sparsity, which pose new challenges in utilizing these data effectively. In this study, we propagated the discrete somatic mutation data of pancreatic cancer through a network propagation model based on protein–protein interaction networks. This resulted in smoothed somatic mutation profile data that incorporate protein network information. Based on this smoothed mutation profile data, we obtained the activity levels of different metabolic pathways in pancreatic cancer patients. Subsequently, using the activity levels of various metabolic pathways in cancer patients, we employed a deep clustering algorithm to establish biologically and clinically relevant metabolic subtypes of pancreatic cancer. Our study holds scientific significance in classifying pancreatic cancer based on somatic mutation data and may provide a crucial theoretical basis for the diagnosis and immunotherapy of pancreatic cancer patients.
Urinary glyphosate levels and association with mortality in the 2013–16 National Health and Nutrition Examination Survey
Authors: Untalan Matthew , Ivic-Pavlicic Tara , Taioli Emanuela 
Published: December 2023

Abstract

Objectives
Glyphosate is the most commonly used herbicide in the USA; however, its safety is still under debate. We assessed glyphosate levels and their association with overall mortality in a representative sample of the US adult population from the 2013 to 2016 National Health and Nutrition Examination Survey.

Methods
We extracted data on urinary glyphosate (N = 2910) measured by ion chromatography isotope-dilution tandem mass spectrometry. Associations between glyphosate concentrations and demographic, lifestyle and other exposures were analyzed. Data were linked to public-use Mortality Files for 2019.

Results
The mean (STD) glyphosate level was 0.53 (0.59) ng/ml, with 25.7% of the subjects having glyphosate levels at or below the detection limit. At multivariate analysis, age and creatinine were associated with glyphosate urinary levels (both P &lt; 0.0001). There was a borderline association between glyphosate levels and mortality (HRadj 1.33; 95% CI 0.99–1.77 P = 0.06). When 3,5,6-trichloropyridinol was excluded from the Cox model, glyphosate exhibits a significant association with mortality (HRadj 1.33; 95% CI 1.00–1.77; P = 0.0532).

Conclusions
These nationally representative data suggest that recent exposure to glyphosate could be associated with increased mortality. More studies are necessary to understand population-level risk associated with the product, given its widespread use in agriculture.
Functional and anatomical connectivity predict brain stimulation’s mnemonic effects
Authors: Ezzyat Youssef , Kragel James E , Solomon Ethan A , Lega Bradley C , Aronson Joshua P , Jobst Barbara C , Gross Robert E , Sperling Michael R , Worrell Gregory A , Sheth Sameer A , Wanda Paul A , Rizzuto Daniel S , Kahana Michael J 
Published: December 2023

Abstract
Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation’s behavioral and physiological effects depend on the stimulation target’s anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered the stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain’s memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation’s behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.
Anonymization of face images with Contrastive Learning
Authors: Xu Xintong , Cui Run , Huang Chanying , Yan Kedong 
Published: December 2023

Abstract
Photos or videos taken by individuals often carry sensitive details such as facial identities, which has led to an escalating societal interest in privacy protection measures. We suggest an improved face identity transformer that offers password-protected anonymization and de-anonymization of photo-realistic facial images in visual data. Our face identity transformer is designed to (1) erase facial identity information after anonymization, (2) restore the original face when a correct password is provided and (3) generate an incorrect but realistic face when given an incorrect password. The processes of image anonymization and de-anonymization are facilitated through a password scheme, a multi-task learning objective and generative adversarial networks comprising InfoGAN and contrastive learning. In-depth experiments indicate that our methodology can execute anonymization and de-anonymization based on password conditions whilst reducing training time and enhancing image quality compared to existing anonymization procedures. Additionally, it maintains a recognition rate as low as 4.8% for anonymized images without sacrificing the face detection rate of the original method.
Design of the formalized and integrated Alzheimer’s Disease Ontology and its application in retrieving textual data via text mining
Authors: Zhang Bide , Lage-Rupprecht Vanessa , Wegner Philipp , Sargsyan Astghik , Gebel Stephan , Jacobs Marc , Klein Jürgen , Hofmann-Apitius Martin , Tom Kodamullil Alpha 
Published: December 2023

Abstract
As one of the leading causes for dementia in the population, it is imperative that we discern exactly why Alzheimer’s disease (AD) has a strong molecular association with beta-amyloid and tau. Although a clear understanding about etiology and pathogenesis of AD remains unsolved, scientists worldwide have dedicated significant efforts to discovering the molecular interactions linked to the pathological characteristics and potential treatments. Knowledge representations, such as domain ontologies encompassing our current understanding about AD, could greatly assist and contribute to disease research. This paper describes the construction and application of the integrated Alzheimer’s Disease Ontology (ADO), combining selected concepts from the former version of the ADO and the Alzheimer’s Disease Mapping Ontology (ADMO). In addition to the existing entities available from these knowledge models, essential knowledge about AD from public sources, such as newly discovered risk factor genes and novel treatments, was also integrated. The ADO can also be leveraged in text mining scenarios given that it is conceptually enriched with domain-specific knowledge as well as their relations. The integrated ADO consists of 39 855 total axioms. The ontology covers many aspects of the AD domain, including risk factor genes, clinical features, treatments and experimental models. The ontology complies with the Open Biological and Biomedical Ontology principles and was accepted by the foundry. In this paper, we illustrate the role of the presented ontology in extracting textual information from the SCAIView database and key measures in an ADO-based corpus.
Database URL: https://academic.oup.com/database
Peoples, Inhabitants and Workers: Colonialism in the Treaty of Rome
Authors: Eklund Hanna 
Published: December 2023

Abstract
In 1957, when the Treaty of Rome was signed, founding the European Economic Community (EEC), which later became the European Union (EU), four out of six of the original member states were colonial powers. This article uses archival material from the Treaty of Rome negotiations to interrogate ways in which the colonial politics of the time shaped the drafting of legal categories describing individuals: those of peoples, inhabitants and workers. As the Treaty of Rome ‘associated’ colonized territories to the EEC, this article shows how the treaty simultaneously arranged its legal categories to exclude individuals who lived in colonized territories from legal benefits and representation. This article situates the EU as an example of a post-World War II international organization, with its founding legal texts shaped by colonialism.
John Sheppard and the Ewens: a closer look
Authors: Smart Jason 
Published: December 2023

Abstract
The known musical career of John Sheppard spans just 15 years. In 1543, when he was probably still in his late twenties, he was appointed informator choristarum of Magdalen College, Oxford. At his death in 1558, at about the age of 43, he was a Gentleman of the Chapel Royal, perhaps having been appointed on leaving Oxford in 1548. A recent article draws attention to the fact that, early in the reign of Queen Mary, Sheppard and his family were involved in a legal action concerning a group of properties in the parish of St Clement Danes, Middlesex. Deeper investigation of this dispute reveals where Sheppard’s geographical ties lay shortly before his Oxford appointment. It allows us to pinpoint with a high degree of confidence when and where his first marriage took place and to understand a little of the young couple’s circumstances. A separate action, in which he appeared as a joint plaintiff with his Chapel Royal colleague Luke Caustell, is less revealing, but potentially points to a connection with the same geographical region of England.